Overview

Dataset statistics

Number of variables75
Number of observations107291
Missing cells4763396
Missing cells (%)59.2%
Duplicate rows4
Duplicate rows (%)< 0.1%
Total size in memory60.0 MiB
Average record size in memory586.0 B

Variable types

Text52
Numeric18
Boolean2
Unsupported3

Alerts

Currency has constant value ""Constant
Dataset has 4 (< 0.1%) duplicate rowsDuplicates
Subtotal is highly overall correlated with Total and 1 other fieldsHigh correlation
Taxes is highly overall correlated with Tax 1 Value and 5 other fieldsHigh correlation
Total is highly overall correlated with Subtotal and 1 other fieldsHigh correlation
Lineitem price is highly overall correlated with Lineitem compare at priceHigh correlation
Lineitem compare at price is highly overall correlated with Lineitem priceHigh correlation
Tax 1 Value is highly overall correlated with Taxes and 2 other fieldsHigh correlation
Tax 2 Value is highly overall correlated with TaxesHigh correlation
Tax 3 Value is highly overall correlated with Taxes and 1 other fieldsHigh correlation
Tax 4 Value is highly overall correlated with TaxesHigh correlation
Tax 5 Value is highly overall correlated with Taxes and 1 other fieldsHigh correlation
Duties is highly overall correlated with Subtotal and 5 other fieldsHigh correlation
Lineitem requires shipping is highly overall correlated with Lineitem taxableHigh correlation
Lineitem taxable is highly overall correlated with Duties and 1 other fieldsHigh correlation
Lineitem taxable is highly imbalanced (58.5%)Imbalance
Financial Status has 60909 (56.8%) missing valuesMissing
Paid at has 66655 (62.1%) missing valuesMissing
Fulfillment Status has 60909 (56.8%) missing valuesMissing
Fulfilled at has 62380 (58.1%) missing valuesMissing
Accepts Marketing has 60909 (56.8%) missing valuesMissing
Currency has 60909 (56.8%) missing valuesMissing
Subtotal has 60909 (56.8%) missing valuesMissing
Shipping has 60909 (56.8%) missing valuesMissing
Taxes has 60909 (56.8%) missing valuesMissing
Total has 60909 (56.8%) missing valuesMissing
Discount Code has 76375 (71.2%) missing valuesMissing
Discount Amount has 60909 (56.8%) missing valuesMissing
Shipping Method has 61696 (57.5%) missing valuesMissing
Lineitem compare at price has 78374 (73.0%) missing valuesMissing
Billing Name has 60998 (56.9%) missing valuesMissing
Billing Street has 60930 (56.8%) missing valuesMissing
Billing Address1 has 60932 (56.8%) missing valuesMissing
Billing Address2 has 96687 (90.1%) missing valuesMissing
Billing Company has 106353 (99.1%) missing valuesMissing
Billing City has 60929 (56.8%) missing valuesMissing
Billing Zip has 61004 (56.9%) missing valuesMissing
Billing Province has 61597 (57.4%) missing valuesMissing
Billing Country has 60928 (56.8%) missing valuesMissing
Billing Phone has 65410 (61.0%) missing valuesMissing
Shipping Name has 61258 (57.1%) missing valuesMissing
Shipping Street has 61249 (57.1%) missing valuesMissing
Shipping Address1 has 61251 (57.1%) missing valuesMissing
Shipping Address2 has 95615 (89.1%) missing valuesMissing
Shipping Company has 106309 (99.1%) missing valuesMissing
Shipping City has 61248 (57.1%) missing valuesMissing
Shipping Zip has 61301 (57.1%) missing valuesMissing
Shipping Province has 61866 (57.7%) missing valuesMissing
Shipping Country has 61249 (57.1%) missing valuesMissing
Shipping Phone has 62096 (57.9%) missing valuesMissing
Notes has 94999 (88.5%) missing valuesMissing
Note Attributes has 88473 (82.5%) missing valuesMissing
Cancelled at has 106067 (98.9%) missing valuesMissing
Payment Method has 66614 (62.1%) missing valuesMissing
Payment Reference has 66616 (62.1%) missing valuesMissing
Refunded Amount has 60909 (56.8%) missing valuesMissing
Id has 60909 (56.8%) missing valuesMissing
Tags has 87907 (81.9%) missing valuesMissing
Risk Level has 60909 (56.8%) missing valuesMissing
Source has 60909 (56.8%) missing valuesMissing
Tax 1 Name has 75199 (70.1%) missing valuesMissing
Tax 1 Value has 75199 (70.1%) missing valuesMissing
Tax 2 Name has 87548 (81.6%) missing valuesMissing
Tax 2 Value has 87548 (81.6%) missing valuesMissing
Tax 3 Name has 97868 (91.2%) missing valuesMissing
Tax 3 Value has 97868 (91.2%) missing valuesMissing
Tax 4 Name has 102809 (95.8%) missing valuesMissing
Tax 4 Value has 102809 (95.8%) missing valuesMissing
Tax 5 Name has 105804 (98.6%) missing valuesMissing
Tax 5 Value has 105804 (98.6%) missing valuesMissing
Phone has 101454 (94.6%) missing valuesMissing
Receipt Number has 107291 (100.0%) missing valuesMissing
Duties has 107035 (99.8%) missing valuesMissing
Billing Province Name has 61597 (57.4%) missing valuesMissing
Shipping Province Name has 61866 (57.7%) missing valuesMissing
Payment ID has 66614 (62.1%) missing valuesMissing
Payment Terms Name has 107291 (100.0%) missing valuesMissing
Next Payment Due At has 107291 (100.0%) missing valuesMissing
Payment References has 66614 (62.1%) missing valuesMissing
Lineitem quantity is highly skewed (γ1 = 294.8334066)Skewed
Receipt Number is an unsupported type, check if it needs cleaning or further analysisUnsupported
Payment Terms Name is an unsupported type, check if it needs cleaning or further analysisUnsupported
Next Payment Due At is an unsupported type, check if it needs cleaning or further analysisUnsupported
Subtotal has 5126 (4.8%) zerosZeros
Shipping has 39288 (36.6%) zerosZeros
Taxes has 25305 (23.6%) zerosZeros
Total has 3850 (3.6%) zerosZeros
Discount Amount has 14779 (13.8%) zerosZeros
Lineitem compare at price has 1620 (1.5%) zerosZeros
Refunded Amount has 40995 (38.2%) zerosZeros
Lineitem discount has 105679 (98.5%) zerosZeros
Tax 1 Value has 11708 (10.9%) zerosZeros
Tax 2 Value has 2092 (1.9%) zerosZeros

Reproduction

Analysis started2024-02-02 20:37:59.628325
Analysis finished2024-02-02 20:38:30.747119
Duration31.12 seconds
Software versionydata-profiling vv4.6.1
Download configurationconfig.json

Variables

Name
Text

Distinct46381
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:30.857292image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length23
Median length6
Mean length6.2096914
Min length6

Characters and Unicode

Total characters666244
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15341 ?
Unique (%)14.3%

Sample

1st row#75662
2nd row#75662
3rd row#75662
4th row#75661
5th row#75661
ValueCountFrequency (%)
44501 30
 
< 0.1%
75194 30
 
< 0.1%
35767 30
 
< 0.1%
38829 28
 
< 0.1%
49446 26
 
< 0.1%
69692 23
 
< 0.1%
36526 22
 
< 0.1%
62575 22
 
< 0.1%
29775 22
 
< 0.1%
47004 20
 
< 0.1%
Other values (46371) 107038
99.8%
2024-02-02T12:38:31.064819image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
# 102981
15.5%
5 67527
10.1%
4 65537
9.8%
6 65091
9.8%
3 64599
9.7%
7 56028
8.4%
1 48504
7.3%
2 44887
6.7%
0 44311
6.7%
9 43265
6.5%
Other values (5) 63514
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 541081
81.2%
Other Punctuation 102981
 
15.5%
Uppercase Letter 12930
 
1.9%
Dash Punctuation 9252
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 67527
12.5%
4 65537
12.1%
6 65091
12.0%
3 64599
11.9%
7 56028
10.4%
1 48504
9.0%
2 44887
8.3%
0 44311
8.2%
9 43265
8.0%
8 41332
7.6%
Uppercase Letter
ValueCountFrequency (%)
E 4310
33.3%
X 4310
33.3%
C 4310
33.3%
Other Punctuation
ValueCountFrequency (%)
# 102981
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 653314
98.1%
Latin 12930
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
# 102981
15.8%
5 67527
10.3%
4 65537
10.0%
6 65091
10.0%
3 64599
9.9%
7 56028
8.6%
1 48504
7.4%
2 44887
6.9%
0 44311
6.8%
9 43265
6.6%
Other values (2) 50584
7.7%
Latin
ValueCountFrequency (%)
E 4310
33.3%
X 4310
33.3%
C 4310
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 666244
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
# 102981
15.5%
5 67527
10.1%
4 65537
9.8%
6 65091
9.8%
3 64599
9.7%
7 56028
8.4%
1 48504
7.3%
2 44887
6.7%
0 44311
6.7%
9 43265
6.5%
Other values (5) 63514
9.5%

Email
Text

Distinct30911
Distinct (%)28.9%
Missing286
Missing (%)0.3%
Memory size838.3 KiB
2024-02-02T12:38:31.193379image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length37
Mean length21.867829
Min length10

Characters and Unicode

Total characters2339967
Distinct characters67
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6518 ?
Unique (%)6.1%

Sample

1st rowamomda16@gmail.com
2nd rowamomda16@gmail.com
3rd rowamomda16@gmail.com
4th rowkmgnadinger@gmail.com
5th rowkmgnadinger@gmail.com
ValueCountFrequency (%)
roselarougefb@gmail.com 204
 
0.2%
rose1algreen@gmail.com 200
 
0.2%
hnpavone@gmail.com 131
 
0.1%
avril020@gmail.com 130
 
0.1%
jmro9484@gmail.com 118
 
0.1%
ucfdate@yahoo.com 82
 
0.1%
bcwright@gbta.net 73
 
0.1%
talktoshayne@gmail.com 68
 
0.1%
cdikibo@alumni.nd.edu 68
 
0.1%
shiannegrose@gmail.com 67
 
0.1%
Other values (30676) 105864
98.9%
2024-02-02T12:38:31.386376image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 232647
 
9.9%
m 225058
 
9.6%
o 201314
 
8.6%
i 162208
 
6.9%
l 160723
 
6.9%
c 146651
 
6.3%
. 134925
 
5.8%
e 126600
 
5.4%
@ 107005
 
4.6%
g 95198
 
4.1%
Other values (57) 747638
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1959269
83.7%
Other Punctuation 241930
 
10.3%
Decimal Number 121231
 
5.2%
Uppercase Letter 12864
 
0.5%
Connector Punctuation 4044
 
0.2%
Dash Punctuation 587
 
< 0.1%
Math Symbol 42
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 232647
11.9%
m 225058
11.5%
o 201314
10.3%
i 162208
 
8.3%
l 160723
 
8.2%
c 146651
 
7.5%
e 126600
 
6.5%
g 95198
 
4.9%
n 91025
 
4.6%
r 82021
 
4.2%
Other values (16) 435824
22.2%
Uppercase Letter
ValueCountFrequency (%)
A 1463
 
11.4%
M 1327
 
10.3%
C 1023
 
8.0%
O 998
 
7.8%
L 967
 
7.5%
E 681
 
5.3%
I 663
 
5.2%
S 640
 
5.0%
N 582
 
4.5%
R 508
 
3.9%
Other values (16) 4012
31.2%
Decimal Number
ValueCountFrequency (%)
1 23762
19.6%
2 17585
14.5%
0 15977
13.2%
9 13598
11.2%
3 10120
8.3%
7 8891
 
7.3%
8 8854
 
7.3%
4 8123
 
6.7%
5 7489
 
6.2%
6 6832
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 134925
55.8%
@ 107005
44.2%
Connector Punctuation
ValueCountFrequency (%)
_ 4044
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 587
100.0%
Math Symbol
ValueCountFrequency (%)
+ 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1972133
84.3%
Common 367834
 
15.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 232647
11.8%
m 225058
11.4%
o 201314
10.2%
i 162208
 
8.2%
l 160723
 
8.1%
c 146651
 
7.4%
e 126600
 
6.4%
g 95198
 
4.8%
n 91025
 
4.6%
r 82021
 
4.2%
Other values (42) 448688
22.8%
Common
ValueCountFrequency (%)
. 134925
36.7%
@ 107005
29.1%
1 23762
 
6.5%
2 17585
 
4.8%
0 15977
 
4.3%
9 13598
 
3.7%
3 10120
 
2.8%
7 8891
 
2.4%
8 8854
 
2.4%
4 8123
 
2.2%
Other values (5) 18994
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2339967
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 232647
 
9.9%
m 225058
 
9.6%
o 201314
 
8.6%
i 162208
 
6.9%
l 160723
 
6.9%
c 146651
 
6.3%
. 134925
 
5.8%
e 126600
 
5.4%
@ 107005
 
4.6%
g 95198
 
4.1%
Other values (57) 747638
32.0%

Financial Status
Text

MISSING 

Distinct7
Distinct (%)< 0.1%
Missing60909
Missing (%)56.8%
Memory size838.3 KiB
2024-02-02T12:38:31.460141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length18
Median length4
Mean length5.3876073
Min length4

Characters and Unicode

Total characters249888
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowpaid
2nd rowrefunded
3rd rowpaid
4th rowpaid
5th rowpaid
ValueCountFrequency (%)
paid 40961
88.3%
partially_refunded 4268
 
9.2%
refunded 1102
 
2.4%
voided 26
 
0.1%
expired 14
 
< 0.1%
partially_paid 10
 
< 0.1%
authorized 1
 
< 0.1%
2024-02-02T12:38:31.573637image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 51778
20.7%
a 49528
19.8%
i 45290
18.1%
p 45263
18.1%
e 10795
 
4.3%
r 9663
 
3.9%
l 8556
 
3.4%
u 5371
 
2.1%
f 5370
 
2.1%
n 5370
 
2.1%
Other values (8) 12904
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 245610
98.3%
Connector Punctuation 4278
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 51778
21.1%
a 49528
20.2%
i 45290
18.4%
p 45263
18.4%
e 10795
 
4.4%
r 9663
 
3.9%
l 8556
 
3.5%
u 5371
 
2.2%
f 5370
 
2.2%
n 5370
 
2.2%
Other values (7) 8626
 
3.5%
Connector Punctuation
ValueCountFrequency (%)
_ 4278
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 245610
98.3%
Common 4278
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 51778
21.1%
a 49528
20.2%
i 45290
18.4%
p 45263
18.4%
e 10795
 
4.4%
r 9663
 
3.9%
l 8556
 
3.5%
u 5371
 
2.2%
f 5370
 
2.2%
n 5370
 
2.2%
Other values (7) 8626
 
3.5%
Common
ValueCountFrequency (%)
_ 4278
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 249888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 51778
20.7%
a 49528
19.8%
i 45290
18.1%
p 45263
18.1%
e 10795
 
4.3%
r 9663
 
3.9%
l 8556
 
3.4%
u 5371
 
2.1%
f 5370
 
2.1%
n 5370
 
2.1%
Other values (8) 12904
 
5.2%

Paid at
Text

MISSING 

Distinct40611
Distinct (%)99.9%
Missing66655
Missing (%)62.1%
Memory size838.3 KiB
2024-02-02T12:38:31.694944image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1015900
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40586 ?
Unique (%)99.9%

Sample

1st row2023-12-31 20:45:05 -0800
2nd row2023-12-31 19:17:28 -0800
3rd row2023-12-31 18:46:11 -0800
4th row2023-12-31 17:17:54 -0800
5th row2023-12-31 17:17:48 -0800
ValueCountFrequency (%)
0700 25773
 
21.1%
0800 14863
 
12.2%
2023-11-24 638
 
0.5%
2023-11-27 407
 
0.3%
2023-03-29 357
 
0.3%
2023-04-27 281
 
0.2%
2023-11-25 280
 
0.2%
2022-07-04 258
 
0.2%
2023-11-23 256
 
0.2%
2022-11-25 253
 
0.2%
Other values (31582) 78542
64.4%
2024-02-02T12:38:31.872246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 246361
24.3%
2 154415
15.2%
- 121908
12.0%
1 89209
 
8.8%
81272
 
8.0%
: 81272
 
8.0%
3 56841
 
5.6%
7 45744
 
4.5%
4 34036
 
3.4%
8 33973
 
3.3%
Other values (3) 70869
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 731448
72.0%
Dash Punctuation 121908
 
12.0%
Space Separator 81272
 
8.0%
Other Punctuation 81272
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 246361
33.7%
2 154415
21.1%
1 89209
 
12.2%
3 56841
 
7.8%
7 45744
 
6.3%
4 34036
 
4.7%
8 33973
 
4.6%
5 32912
 
4.5%
9 19214
 
2.6%
6 18743
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 121908
100.0%
Space Separator
ValueCountFrequency (%)
81272
100.0%
Other Punctuation
ValueCountFrequency (%)
: 81272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1015900
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 246361
24.3%
2 154415
15.2%
- 121908
12.0%
1 89209
 
8.8%
81272
 
8.0%
: 81272
 
8.0%
3 56841
 
5.6%
7 45744
 
4.5%
4 34036
 
3.4%
8 33973
 
3.3%
Other values (3) 70869
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1015900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 246361
24.3%
2 154415
15.2%
- 121908
12.0%
1 89209
 
8.8%
81272
 
8.0%
: 81272
 
8.0%
3 56841
 
5.6%
7 45744
 
4.5%
4 34036
 
3.4%
8 33973
 
3.3%
Other values (3) 70869
 
7.0%

Fulfillment Status
Text

MISSING 

Distinct4
Distinct (%)< 0.1%
Missing60909
Missing (%)56.8%
Memory size838.3 KiB
2024-02-02T12:38:31.945320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length11
Median length9
Mean length9.0589884
Min length7

Characters and Unicode

Total characters420174
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfulfilled
2nd rowunfulfilled
3rd rowfulfilled
4th rowfulfilled
5th rowfulfilled
ValueCountFrequency (%)
fulfilled 44911
96.8%
unfulfilled 1401
 
3.0%
restocked 37
 
0.1%
partial 33
 
0.1%
2024-02-02T12:38:32.057995image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 138969
33.1%
f 92624
22.0%
u 47713
 
11.4%
e 46386
 
11.0%
d 46349
 
11.0%
i 46345
 
11.0%
n 1401
 
0.3%
r 70
 
< 0.1%
t 70
 
< 0.1%
a 66
 
< 0.1%
Other values (5) 181
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 420174
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 138969
33.1%
f 92624
22.0%
u 47713
 
11.4%
e 46386
 
11.0%
d 46349
 
11.0%
i 46345
 
11.0%
n 1401
 
0.3%
r 70
 
< 0.1%
t 70
 
< 0.1%
a 66
 
< 0.1%
Other values (5) 181
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 420174
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 138969
33.1%
f 92624
22.0%
u 47713
 
11.4%
e 46386
 
11.0%
d 46349
 
11.0%
i 46345
 
11.0%
n 1401
 
0.3%
r 70
 
< 0.1%
t 70
 
< 0.1%
a 66
 
< 0.1%
Other values (5) 181
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420174
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 138969
33.1%
f 92624
22.0%
u 47713
 
11.4%
e 46386
 
11.0%
d 46349
 
11.0%
i 46345
 
11.0%
n 1401
 
0.3%
r 70
 
< 0.1%
t 70
 
< 0.1%
a 66
 
< 0.1%
Other values (5) 181
 
< 0.1%

Fulfilled at
Text

MISSING 

Distinct43990
Distinct (%)97.9%
Missing62380
Missing (%)58.1%
Memory size838.3 KiB
2024-02-02T12:38:32.180766image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1122775
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43309 ?
Unique (%)96.4%

Sample

1st row2024-01-03 10:20:02 -0800
2nd row2024-01-03 10:20:01 -0800
3rd row2024-01-03 10:20:02 -0800
4th row2024-01-03 10:20:02 -0800
5th row2024-01-03 10:19:59 -0800
ValueCountFrequency (%)
0700 28259
 
21.0%
0800 16652
 
12.4%
2023-10-10 805
 
0.6%
2023-11-29 618
 
0.5%
2023-11-27 570
 
0.4%
2023-12-19 552
 
0.4%
2022-07-25 471
 
0.3%
2022-03-09 431
 
0.3%
2023-10-09 420
 
0.3%
2023-04-04 397
 
0.3%
Other values (24365) 85558
63.5%
2024-02-02T12:38:32.362014image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 290801
25.9%
2 161978
14.4%
- 134733
12.0%
89822
 
8.0%
: 89822
 
8.0%
1 83577
 
7.4%
3 59751
 
5.3%
7 48252
 
4.3%
5 43974
 
3.9%
8 36877
 
3.3%
Other values (3) 83188
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 808398
72.0%
Dash Punctuation 134733
 
12.0%
Space Separator 89822
 
8.0%
Other Punctuation 89822
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 290801
36.0%
2 161978
20.0%
1 83577
 
10.3%
3 59751
 
7.4%
7 48252
 
6.0%
5 43974
 
5.4%
8 36877
 
4.6%
4 34591
 
4.3%
6 27770
 
3.4%
9 20827
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 134733
100.0%
Space Separator
ValueCountFrequency (%)
89822
100.0%
Other Punctuation
ValueCountFrequency (%)
: 89822
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1122775
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 290801
25.9%
2 161978
14.4%
- 134733
12.0%
89822
 
8.0%
: 89822
 
8.0%
1 83577
 
7.4%
3 59751
 
5.3%
7 48252
 
4.3%
5 43974
 
3.9%
8 36877
 
3.3%
Other values (3) 83188
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1122775
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 290801
25.9%
2 161978
14.4%
- 134733
12.0%
89822
 
8.0%
: 89822
 
8.0%
1 83577
 
7.4%
3 59751
 
5.3%
7 48252
 
4.3%
5 43974
 
3.9%
8 36877
 
3.3%
Other values (3) 83188
 
7.4%

Accepts Marketing
Text

MISSING 

Distinct2
Distinct (%)< 0.1%
Missing60909
Missing (%)56.8%
Memory size838.3 KiB
2024-02-02T12:38:32.427904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.6207365
Min length2

Characters and Unicode

Total characters121555
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowno
2nd rowyes
3rd rowyes
4th rowyes
5th rowyes
ValueCountFrequency (%)
yes 28791
62.1%
no 17591
37.9%
2024-02-02T12:38:32.531072image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
y 28791
23.7%
e 28791
23.7%
s 28791
23.7%
n 17591
14.5%
o 17591
14.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 121555
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
y 28791
23.7%
e 28791
23.7%
s 28791
23.7%
n 17591
14.5%
o 17591
14.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 121555
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
y 28791
23.7%
e 28791
23.7%
s 28791
23.7%
n 17591
14.5%
o 17591
14.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121555
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
y 28791
23.7%
e 28791
23.7%
s 28791
23.7%
n 17591
14.5%
o 17591
14.5%

Currency
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing60909
Missing (%)56.8%
Memory size838.3 KiB
2024-02-02T12:38:32.583216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters139146
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSD
2nd rowUSD
3rd rowUSD
4th rowUSD
5th rowUSD
ValueCountFrequency (%)
usd 46382
100.0%
2024-02-02T12:38:32.678355image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 46382
33.3%
S 46382
33.3%
D 46382
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 139146
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 46382
33.3%
S 46382
33.3%
D 46382
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 139146
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 46382
33.3%
S 46382
33.3%
D 46382
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 139146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 46382
33.3%
S 46382
33.3%
D 46382
33.3%

Subtotal
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct6615
Distinct (%)14.3%
Missing60909
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean151.46541
Minimum0
Maximum2337.54
Zeros5126
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:32.745320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q186.52
median150.98
Q3192.98
95-th percentile336
Maximum2337.54
Range2337.54
Interquartile range (IQR)106.46

Descriptive statistics

Standard deviation112.4084
Coefficient of variation (CV)0.74213906
Kurtosis19.027409
Mean151.46541
Median Absolute Deviation (MAD)52.98
Skewness2.3410318
Sum7025268.8
Variance12635.648
MonotonicityNot monotonic
2024-02-02T12:38:32.802790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5126
 
4.8%
148 849
 
0.8%
152 770
 
0.7%
180 708
 
0.7%
156 600
 
0.6%
100 574
 
0.5%
150.98 555
 
0.5%
190 548
 
0.5%
154.98 530
 
0.5%
185 509
 
0.5%
Other values (6605) 35613
33.2%
(Missing) 60909
56.8%
ValueCountFrequency (%)
0 5126
4.8%
0.36 1
 
< 0.1%
0.85 1
 
< 0.1%
1 4
 
< 0.1%
1.01 1
 
< 0.1%
1.15 4
 
< 0.1%
1.25 12
 
< 0.1%
1.32 5
 
< 0.1%
1.49 1
 
< 0.1%
1.52 6
 
< 0.1%
ValueCountFrequency (%)
2337.54 1
< 0.1%
2218.5 1
< 0.1%
2051.25 1
< 0.1%
1743.13 1
< 0.1%
1690 1
< 0.1%
1677.58 1
< 0.1%
1483.95 1
< 0.1%
1448 1
< 0.1%
1423.48 1
< 0.1%
1407.12 1
< 0.1%

Shipping
Real number (ℝ)

MISSING  ZEROS 

Distinct745
Distinct (%)1.6%
Missing60909
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean3.5150164
Minimum0
Maximum420.64
Zeros39288
Zeros (%)36.6%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:32.861256image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile14.77
Maximum420.64
Range420.64
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.158864
Coefficient of variation (CV)3.743614
Kurtosis68.252908
Mean3.5150164
Median Absolute Deviation (MAD)0
Skewness6.1764682
Sum163033.49
Variance173.15571
MonotonicityNot monotonic
2024-02-02T12:38:32.916798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39288
36.6%
9 2590
 
2.4%
6 1806
 
1.7%
57.8 257
 
0.2%
49.12 62
 
0.1%
60.73 56
 
0.1%
65.27 48
 
< 0.1%
81.05 46
 
< 0.1%
48.85 43
 
< 0.1%
14.67 38
 
< 0.1%
Other values (735) 2148
 
2.0%
(Missing) 60909
56.8%
ValueCountFrequency (%)
0 39288
36.6%
5 17
 
< 0.1%
6 1806
 
1.7%
6.16 3
 
< 0.1%
6.2 1
 
< 0.1%
6.94 1
 
< 0.1%
6.98 1
 
< 0.1%
9 2590
 
2.4%
9.39 1
 
< 0.1%
9.4 1
 
< 0.1%
ValueCountFrequency (%)
420.64 1
< 0.1%
344.21 1
< 0.1%
279.98 1
< 0.1%
260.85 1
< 0.1%
255.5 1
< 0.1%
252.22 1
< 0.1%
190.99 1
< 0.1%
175.29 1
< 0.1%
174.38 1
< 0.1%
170.64 1
< 0.1%

Taxes
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct3396
Distinct (%)7.3%
Missing60909
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean5.9784403
Minimum0
Maximum148.42
Zeros25305
Zeros (%)23.6%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:32.974181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q311.1
95-th percentile21.56
Maximum148.42
Range148.42
Interquartile range (IQR)11.1

Descriptive statistics

Standard deviation8.7534022
Coefficient of variation (CV)1.4641615
Kurtosis11.345678
Mean5.9784403
Median Absolute Deviation (MAD)0
Skewness2.3121391
Sum277292.02
Variance76.62205
MonotonicityNot monotonic
2024-02-02T12:38:33.031181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25305
23.6%
8.88 131
 
0.1%
10.36 123
 
0.1%
10.64 116
 
0.1%
10.8 112
 
0.1%
11.4 112
 
0.1%
12.6 108
 
0.1%
9.12 97
 
0.1%
12.95 93
 
0.1%
11.7 92
 
0.1%
Other values (3386) 20093
 
18.7%
(Missing) 60909
56.8%
ValueCountFrequency (%)
0 25305
23.6%
0.03 1
 
< 0.1%
0.04 1
 
< 0.1%
0.06 1
 
< 0.1%
0.07 4
 
< 0.1%
0.08 2
 
< 0.1%
0.09 10
 
< 0.1%
0.1 10
 
< 0.1%
0.11 15
 
< 0.1%
0.12 8
 
< 0.1%
ValueCountFrequency (%)
148.42 1
< 0.1%
128.94 1
< 0.1%
120.37 1
< 0.1%
116.2 1
< 0.1%
109.05 1
< 0.1%
104.59 1
< 0.1%
103.08 1
< 0.1%
101.36 1
< 0.1%
100.8 1
< 0.1%
88.07 1
< 0.1%

Total
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct15416
Distinct (%)33.2%
Missing60909
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean160.90137
Minimum0
Maximum2337.54
Zeros3850
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:33.090348image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q190.74
median156
Q3204.89
95-th percentile358.076
Maximum2337.54
Range2337.54
Interquartile range (IQR)114.15

Descriptive statistics

Standard deviation118.40811
Coefficient of variation (CV)0.73590488
Kurtosis17.981631
Mean160.90137
Median Absolute Deviation (MAD)56.365
Skewness2.346134
Sum7462927.5
Variance14020.48
MonotonicityNot monotonic
2024-02-02T12:38:33.147462image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3850
 
3.6%
148 382
 
0.4%
152 368
 
0.3%
180 353
 
0.3%
100 346
 
0.3%
150.98 288
 
0.3%
156 282
 
0.3%
190 278
 
0.3%
154.98 274
 
0.3%
185 241
 
0.2%
Other values (15406) 39720
37.0%
(Missing) 60909
56.8%
ValueCountFrequency (%)
0 3850
3.6%
0.07 1
 
< 0.1%
0.27 1
 
< 0.1%
0.28 1
 
< 0.1%
0.36 1
 
< 0.1%
0.39 1
 
< 0.1%
0.47 1
 
< 0.1%
0.52 1
 
< 0.1%
0.67 1
 
< 0.1%
0.79 1
 
< 0.1%
ValueCountFrequency (%)
2337.54 1
< 0.1%
2218.5 1
< 0.1%
2051.25 1
< 0.1%
1891.18 1
< 0.1%
1690 1
< 0.1%
1677.58 1
< 0.1%
1654.59 1
< 0.1%
1596.42 1
< 0.1%
1530.52 1
< 0.1%
1516.17 1
< 0.1%

Discount Code
Text

MISSING 

Distinct4297
Distinct (%)13.9%
Missing76375
Missing (%)71.2%
Memory size838.3 KiB
2024-02-02T12:38:33.283188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length58
Median length54
Mean length12.254852
Min length2

Characters and Unicode

Total characters378871
Distinct characters82
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3899 ?
Unique (%)12.6%

Sample

1st rowRWRD1UMFXV92IH
2nd rowWELCOMEBACK20
3rd rowWELCOME20PASHION
4th rowWELCOME20PASHION
5th rowTIKTOK20
ValueCountFrequency (%)
welcome20pashion 9413
28.0%
loop-discount 3109
 
9.2%
bf30 1136
 
3.4%
pashion20 830
 
2.5%
welcome20 713
 
2.1%
honey15 566
 
1.7%
515
 
1.5%
tiktok20 489
 
1.5%
mrktg 405
 
1.2%
replacement 387
 
1.2%
Other values (4204) 16076
47.8%
2024-02-02T12:38:33.504188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 30492
 
8.0%
O 25434
 
6.7%
0 17795
 
4.7%
A 17027
 
4.5%
2 16783
 
4.4%
I 15754
 
4.2%
L 15339
 
4.0%
W 14706
 
3.9%
M 14321
 
3.8%
H 14221
 
3.8%
Other values (72) 196999
52.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 245384
64.8%
Lowercase Letter 74491
 
19.7%
Decimal Number 51322
 
13.5%
Dash Punctuation 4565
 
1.2%
Space Separator 2780
 
0.7%
Other Punctuation 291
 
0.1%
Close Punctuation 19
 
< 0.1%
Open Punctuation 15
 
< 0.1%
Math Symbol 2
 
< 0.1%
Currency Symbol 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 30492
12.4%
O 25434
 
10.4%
A 17027
 
6.9%
I 15754
 
6.4%
L 15339
 
6.3%
W 14706
 
6.0%
M 14321
 
5.8%
H 14221
 
5.8%
N 14151
 
5.8%
P 13784
 
5.6%
Other values (17) 70155
28.6%
Lowercase Letter
ValueCountFrequency (%)
o 12367
16.6%
n 5638
 
7.6%
e 5544
 
7.4%
s 5430
 
7.3%
t 5427
 
7.3%
c 5216
 
7.0%
i 5081
 
6.8%
d 4864
 
6.5%
l 4752
 
6.4%
u 4324
 
5.8%
Other values (16) 15848
21.3%
Other Punctuation
ValueCountFrequency (%)
. 150
51.5%
# 61
21.0%
% 21
 
7.2%
/ 20
 
6.9%
, 14
 
4.8%
& 8
 
2.7%
! 6
 
2.1%
: 5
 
1.7%
' 2
 
0.7%
" 2
 
0.7%
Other values (2) 2
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 17795
34.7%
2 16783
32.7%
5 3939
 
7.7%
3 3913
 
7.6%
1 2611
 
5.1%
7 1917
 
3.7%
4 1525
 
3.0%
8 988
 
1.9%
9 951
 
1.9%
6 900
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 4565
100.0%
Space Separator
ValueCountFrequency (%)
2780
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 319875
84.4%
Common 58996
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 30492
 
9.5%
O 25434
 
8.0%
A 17027
 
5.3%
I 15754
 
4.9%
L 15339
 
4.8%
W 14706
 
4.6%
M 14321
 
4.5%
H 14221
 
4.4%
N 14151
 
4.4%
P 13784
 
4.3%
Other values (43) 144646
45.2%
Common
ValueCountFrequency (%)
0 17795
30.2%
2 16783
28.4%
- 4565
 
7.7%
5 3939
 
6.7%
3 3913
 
6.6%
2780
 
4.7%
1 2611
 
4.4%
7 1917
 
3.2%
4 1525
 
2.6%
8 988
 
1.7%
Other values (19) 2180
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 378868
> 99.9%
None 2
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 30492
 
8.0%
O 25434
 
6.7%
0 17795
 
4.7%
A 17027
 
4.5%
2 16783
 
4.4%
I 15754
 
4.2%
L 15339
 
4.0%
W 14706
 
3.9%
M 14321
 
3.8%
H 14221
 
3.8%
Other values (70) 196996
52.0%
None
ValueCountFrequency (%)
Ü 2
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%

Discount Amount
Real number (ℝ)

MISSING  ZEROS 

Distinct3255
Distinct (%)7.0%
Missing60909
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean45.055663
Minimum0
Maximum3505
Zeros14779
Zeros (%)13.8%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:33.582972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median34.5
Q352.5
95-th percentile175
Maximum3505
Range3505
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation66.94735
Coefficient of variation (CV)1.4858809
Kurtosis181.18078
Mean45.055663
Median Absolute Deviation (MAD)34.5
Skewness6.6315546
Sum2089771.8
Variance4481.9477
MonotonicityNot monotonic
2024-02-02T12:38:33.641284image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14779
 
13.8%
37 1484
 
1.4%
38 1455
 
1.4%
39 1058
 
1.0%
30 950
 
0.9%
45 912
 
0.9%
40 759
 
0.7%
36 592
 
0.6%
10 501
 
0.5%
15 442
 
0.4%
Other values (3245) 23450
 
21.9%
(Missing) 60909
56.8%
ValueCountFrequency (%)
0 14779
13.8%
0.11 1
 
< 0.1%
0.75 1
 
< 0.1%
0.8 1
 
< 0.1%
0.82 1
 
< 0.1%
0.89 1
 
< 0.1%
1 16
 
< 0.1%
1.2 1
 
< 0.1%
1.28 1
 
< 0.1%
1.4 1
 
< 0.1%
ValueCountFrequency (%)
3505 1
< 0.1%
1304.99 1
< 0.1%
1267.97 1
< 0.1%
1169.98 1
< 0.1%
1047.5 1
< 0.1%
995 1
< 0.1%
945 1
< 0.1%
930 2
< 0.1%
920 1
< 0.1%
915 1
< 0.1%

Shipping Method
Text

MISSING 

Distinct36
Distinct (%)0.1%
Missing61696
Missing (%)57.5%
Memory size838.3 KiB
2024-02-02T12:38:33.705685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length52
Median length38
Mean length35.040991
Min length1

Characters and Unicode

Total characters1597694
Distinct characters54
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)< 0.1%

Sample

1st rowStandard Shipping (5-10 business days)
2nd rowStandard Shipping (5-10 business days)
3rd rowStandard Shipping (5-10 business days)
4th rowStandard Shipping (5-10 business days)
5th rowStandard Shipping (5-10 business days)
ValueCountFrequency (%)
shipping 39365
18.7%
standard 39203
18.6%
5-10 38273
18.2%
business 38273
18.2%
days 38273
18.2%
ground 3854
 
1.8%
fedex 3665
 
1.7%
free 2308
 
1.1%
international 2012
 
1.0%
packet 1421
 
0.7%
Other values (33) 4090
 
1.9%
2024-02-02T12:38:33.838895image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
165142
 
10.3%
s 155064
 
9.7%
n 128604
 
8.0%
a 126798
 
7.9%
d 126644
 
7.9%
i 121079
 
7.6%
p 79905
 
5.0%
S 78456
 
4.9%
e 52395
 
3.3%
r 50223
 
3.1%
Other values (44) 513384
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1103447
69.1%
Space Separator 165142
 
10.3%
Decimal Number 114833
 
7.2%
Uppercase Letter 99396
 
6.2%
Dash Punctuation 38311
 
2.4%
Close Punctuation 38273
 
2.4%
Open Punctuation 38273
 
2.4%
Other Punctuation 10
 
< 0.1%
Other Symbol 5
 
< 0.1%
Connector Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 155064
14.1%
n 128604
11.7%
a 126798
11.5%
d 126644
11.5%
i 121079
11.0%
p 79905
7.2%
e 52395
 
4.7%
r 50223
 
4.6%
t 45656
 
4.1%
u 42143
 
3.8%
Other values (12) 174936
15.9%
Uppercase Letter
ValueCountFrequency (%)
S 78456
78.9%
F 5969
 
6.0%
G 3860
 
3.9%
E 3694
 
3.7%
I 2042
 
2.1%
P 1809
 
1.8%
T 1435
 
1.4%
C 931
 
0.9%
X 576
 
0.6%
M 330
 
0.3%
Other values (10) 294
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 38286
33.3%
1 38273
33.3%
5 38273
33.3%
2 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
& 8
80.0%
' 2
 
20.0%
Space Separator
ValueCountFrequency (%)
165142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38311
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38273
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38273
100.0%
Other Symbol
ValueCountFrequency (%)
® 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1202843
75.3%
Common 394851
 
24.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 155064
12.9%
n 128604
10.7%
a 126798
10.5%
d 126644
10.5%
i 121079
10.1%
p 79905
 
6.6%
S 78456
 
6.5%
e 52395
 
4.4%
r 50223
 
4.2%
t 45656
 
3.8%
Other values (32) 238019
19.8%
Common
ValueCountFrequency (%)
165142
41.8%
- 38311
 
9.7%
0 38286
 
9.7%
1 38273
 
9.7%
5 38273
 
9.7%
) 38273
 
9.7%
( 38273
 
9.7%
& 8
 
< 0.1%
® 5
 
< 0.1%
_ 4
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1597689
> 99.9%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
165142
 
10.3%
s 155064
 
9.7%
n 128604
 
8.0%
a 126798
 
7.9%
d 126644
 
7.9%
i 121079
 
7.6%
p 79905
 
5.0%
S 78456
 
4.9%
e 52395
 
3.3%
r 50223
 
3.1%
Other values (43) 513379
32.1%
None
ValueCountFrequency (%)
® 5
100.0%
Distinct46353
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:33.965161image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2682275
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15318 ?
Unique (%)14.3%

Sample

1st row2023-12-31 20:45:04 -0800
2nd row2023-12-31 20:45:04 -0800
3rd row2023-12-31 20:45:04 -0800
4th row2023-12-31 19:17:26 -0800
5th row2023-12-31 19:17:26 -0800
ValueCountFrequency (%)
0700 66787
 
20.7%
0800 40504
 
12.6%
2023-11-24 1746
 
0.5%
2023-03-29 993
 
0.3%
2023-11-27 973
 
0.3%
2023-11-25 739
 
0.2%
2023-04-27 716
 
0.2%
2023-11-23 698
 
0.2%
2023-12-12 688
 
0.2%
2022-11-28 644
 
0.2%
Other values (34634) 207385
64.4%
2024-02-02T12:38:34.148479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 648659
24.2%
2 407094
15.2%
- 321873
12.0%
1 237767
 
8.9%
214582
 
8.0%
: 214582
 
8.0%
3 152663
 
5.7%
7 118658
 
4.4%
4 90221
 
3.4%
8 89854
 
3.3%
Other values (3) 186322
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1931238
72.0%
Dash Punctuation 321873
 
12.0%
Space Separator 214582
 
8.0%
Other Punctuation 214582
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 648659
33.6%
2 407094
21.1%
1 237767
 
12.3%
3 152663
 
7.9%
7 118658
 
6.1%
4 90221
 
4.7%
8 89854
 
4.7%
5 87087
 
4.5%
9 50342
 
2.6%
6 48893
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 321873
100.0%
Space Separator
ValueCountFrequency (%)
214582
100.0%
Other Punctuation
ValueCountFrequency (%)
: 214582
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2682275
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 648659
24.2%
2 407094
15.2%
- 321873
12.0%
1 237767
 
8.9%
214582
 
8.0%
: 214582
 
8.0%
3 152663
 
5.7%
7 118658
 
4.4%
4 90221
 
3.4%
8 89854
 
3.3%
Other values (3) 186322
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2682275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 648659
24.2%
2 407094
15.2%
- 321873
12.0%
1 237767
 
8.9%
214582
 
8.0%
: 214582
 
8.0%
3 152663
 
5.7%
7 118658
 
4.4%
4 90221
 
3.4%
8 89854
 
3.3%
Other values (3) 186322
 
6.9%

Lineitem quantity
Real number (ℝ)

SKEWED 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0042128
Minimum1
Maximum86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:34.219725image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum86
Range85
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.26890442
Coefficient of variation (CV)0.26777632
Kurtosis93040.35
Mean1.0042128
Median Absolute Deviation (MAD)0
Skewness294.83341
Sum107743
Variance0.072309589
MonotonicityNot monotonic
2024-02-02T12:38:34.258816image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 106985
99.7%
2 260
 
0.2%
3 32
 
< 0.1%
4 10
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
86 1
 
< 0.1%
ValueCountFrequency (%)
1 106985
99.7%
2 260
 
0.2%
3 32
 
< 0.1%
4 10
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
86 1
 
< 0.1%
ValueCountFrequency (%)
86 1
 
< 0.1%
6 1
 
< 0.1%
5 2
 
< 0.1%
4 10
 
< 0.1%
3 32
 
< 0.1%
2 260
 
0.2%
1 106985
99.7%
Distinct8584
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:34.359264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length93
Median length77
Mean length46.478251
Min length14

Characters and Unicode

Total characters4986698
Distinct characters68
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1863 ?
Unique (%)1.7%

Sample

1st rowOnward VIP Protection+ - $8.75
2nd rowStelo Chrome Gold - 6-6.5
3rd rowThe D'Orsay - Forest Velvet + Stiletto Heel Kit 3 Forest Green - 6.5
4th rowStiletto Heel Kit 4 Whiskey - 9-11
5th rowBlock Heel Kit 4 Coal - 9-11
ValueCountFrequency (%)
220835
21.0%
heel 71723
 
6.8%
kit 71470
 
6.8%
block 54628
 
5.2%
the 48262
 
4.6%
4 36085
 
3.4%
3 34859
 
3.3%
coal 33091
 
3.2%
sand 19683
 
1.9%
stiletto 19606
 
1.9%
Other values (296) 439434
41.9%
2024-02-02T12:38:34.556777image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
942877
18.9%
e 418651
 
8.4%
t 305672
 
6.1%
l 258982
 
5.2%
a 247477
 
5.0%
i 235936
 
4.7%
o 222021
 
4.5%
- 215666
 
4.3%
n 159677
 
3.2%
h 126033
 
2.5%
Other values (58) 1853706
37.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2558600
51.3%
Space Separator 942877
 
18.9%
Uppercase Letter 749776
 
15.0%
Decimal Number 351996
 
7.1%
Dash Punctuation 215666
 
4.3%
Other Punctuation 101729
 
2.0%
Math Symbol 42143
 
0.8%
Currency Symbol 23675
 
0.5%
Open Punctuation 118
 
< 0.1%
Close Punctuation 118
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 418651
16.4%
t 305672
11.9%
l 258982
10.1%
a 247477
9.7%
i 235936
9.2%
o 222021
8.7%
n 159677
 
6.2%
h 126033
 
4.9%
r 118422
 
4.6%
c 87650
 
3.4%
Other values (14) 378079
14.8%
Uppercase Letter
ValueCountFrequency (%)
S 104728
14.0%
K 77062
10.3%
H 72880
9.7%
B 72850
9.7%
C 63126
8.4%
L 62366
8.3%
T 54169
 
7.2%
P 38348
 
5.1%
A 28757
 
3.8%
F 24388
 
3.3%
Other values (12) 151102
20.2%
Decimal Number
ValueCountFrequency (%)
5 82489
23.4%
3 40335
11.5%
4 39645
11.3%
8 38691
11.0%
7 37966
10.8%
1 35387
10.1%
0 25185
 
7.2%
6 19159
 
5.4%
9 18871
 
5.4%
2 14268
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 73645
72.4%
& 14896
 
14.6%
, 6168
 
6.1%
' 6167
 
6.1%
/ 754
 
0.7%
" 99
 
0.1%
Space Separator
ValueCountFrequency (%)
942877
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 215666
100.0%
Math Symbol
ValueCountFrequency (%)
+ 42143
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 23675
100.0%
Open Punctuation
ValueCountFrequency (%)
( 118
100.0%
Close Punctuation
ValueCountFrequency (%)
) 118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3308376
66.3%
Common 1678322
33.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 418651
 
12.7%
t 305672
 
9.2%
l 258982
 
7.8%
a 247477
 
7.5%
i 235936
 
7.1%
o 222021
 
6.7%
n 159677
 
4.8%
h 126033
 
3.8%
r 118422
 
3.6%
S 104728
 
3.2%
Other values (36) 1110777
33.6%
Common
ValueCountFrequency (%)
942877
56.2%
- 215666
 
12.9%
5 82489
 
4.9%
. 73645
 
4.4%
+ 42143
 
2.5%
3 40335
 
2.4%
4 39645
 
2.4%
8 38691
 
2.3%
7 37966
 
2.3%
1 35387
 
2.1%
Other values (12) 129478
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4986698
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
942877
18.9%
e 418651
 
8.4%
t 305672
 
6.1%
l 258982
 
5.2%
a 247477
 
5.0%
i 235936
 
4.7%
o 222021
 
4.5%
- 215666
 
4.3%
n 159677
 
3.2%
h 126033
 
2.5%
Other values (58) 1853706
37.2%

Lineitem price
Real number (ℝ)

HIGH CORRELATION 

Distinct3702
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.752632
Minimum0
Maximum507.51
Zeros72
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:34.632481image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.98
Q120
median50
Q3164.99
95-th percentile200
Maximum507.51
Range507.51
Interquartile range (IQR)144.99

Descriptive statistics

Standard deviation75.546535
Coefficient of variation (CV)0.89137685
Kurtosis-1.0244129
Mean84.752632
Median Absolute Deviation (MAD)45.52
Skewness0.58693454
Sum9093194.7
Variance5707.2789
MonotonicityNot monotonic
2024-02-02T12:38:34.845228image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 8013
 
7.5%
50 7018
 
6.5%
185 6768
 
6.3%
190 6355
 
5.9%
2.98 5156
 
4.8%
30 3589
 
3.3%
35 3481
 
3.2%
195 3442
 
3.2%
15 2761
 
2.6%
10 2689
 
2.5%
Other values (3692) 58019
54.1%
ValueCountFrequency (%)
0 72
0.1%
0.67 1
 
< 0.1%
0.82 1
 
< 0.1%
0.89 2
 
< 0.1%
0.93 1
 
< 0.1%
0.98 26
 
< 0.1%
0.99 1
 
< 0.1%
1 2
 
< 0.1%
1.11 2
 
< 0.1%
1.14 1
 
< 0.1%
ValueCountFrequency (%)
507.51 1
 
< 0.1%
500 17
< 0.1%
400 2
 
< 0.1%
350 2
 
< 0.1%
320.26 1
 
< 0.1%
320.25 1
 
< 0.1%
320.16 1
 
< 0.1%
315 33
< 0.1%
304.5 3
 
< 0.1%
300 6
 
< 0.1%

Lineitem compare at price
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct676
Distinct (%)2.3%
Missing78374
Missing (%)73.0%
Infinite0
Infinite (%)0.0%
Mean121.99451
Minimum0
Maximum280.28
Zeros1620
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:34.901687image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q150
median155
Q3190
95-th percentile195
Maximum280.28
Range280.28
Interquartile range (IQR)140

Descriptive statistics

Standard deviation75.523547
Coefficient of variation (CV)0.61907332
Kurtosis-1.6260456
Mean121.99451
Median Absolute Deviation (MAD)40
Skewness-0.24561323
Sum3527715.2
Variance5703.8061
MonotonicityNot monotonic
2024-02-02T12:38:34.955102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190 4777
 
4.5%
50 4601
 
4.3%
195 3555
 
3.3%
185 2819
 
2.6%
40 1864
 
1.7%
0 1620
 
1.5%
35 1447
 
1.3%
155 1278
 
1.2%
150 881
 
0.8%
55 664
 
0.6%
Other values (666) 5411
 
5.0%
(Missing) 78374
73.0%
ValueCountFrequency (%)
0 1620
1.5%
10 248
 
0.2%
10.78 1
 
< 0.1%
15 470
 
0.4%
15.4 1
 
< 0.1%
15.51 2
 
< 0.1%
20 150
 
0.1%
20.64 3
 
< 0.1%
20.9 1
 
< 0.1%
21.34 2
 
< 0.1%
ValueCountFrequency (%)
280.28 1
< 0.1%
280.23 1
< 0.1%
279.83 1
< 0.1%
279.69 2
< 0.1%
279.68 1
< 0.1%
279.57 1
< 0.1%
279.44 1
< 0.1%
279.27 1
< 0.1%
279.26 1
< 0.1%
279.22 1
< 0.1%
Distinct6886
Distinct (%)6.4%
Missing414
Missing (%)0.4%
Memory size838.3 KiB
2024-02-02T12:38:35.051161image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length20
Median length19
Mean length13.019686
Min length8

Characters and Unicode

Total characters1391505
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1064 ?
Unique (%)1.0%

Sample

1st rowONWARDINS40
2nd row665HO21STCHG
3rd row65HO21DOFVS3FG
4th row911HO21HKS4WH
5th row911HO21HKB4CO
ValueCountFrequency (%)
sp-sr-150200 5365
 
5.0%
sp-sr-200250 2654
 
2.5%
sp-sr-100150 2061
 
1.9%
sp-sr-75100 1530
 
1.4%
sp-sr-250300 1044
 
1.0%
785ho21fcta 827
 
0.8%
785ho21fcco 678
 
0.6%
785ho21hkb4sr 581
 
0.5%
785ho21hkb3sr 532
 
0.5%
785ho21hkb3lw 522
 
0.5%
Other values (6876) 91083
85.2%
2024-02-02T12:38:35.225265image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 135289
 
9.7%
2 128899
 
9.3%
H 105337
 
7.6%
O 89541
 
6.4%
1 89287
 
6.4%
5 88250
 
6.3%
B 72954
 
5.2%
P 56324
 
4.0%
L 50354
 
3.6%
0 46304
 
3.3%
Other values (26) 528966
38.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 822159
59.1%
Decimal Number 539400
38.8%
Dash Punctuation 29792
 
2.1%
Lowercase Letter 154
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 135289
16.5%
H 105337
12.8%
O 89541
10.9%
B 72954
8.9%
P 56324
 
6.9%
L 50354
 
6.1%
C 44711
 
5.4%
A 42440
 
5.2%
K 39950
 
4.9%
T 37603
 
4.6%
Other values (14) 147656
18.0%
Decimal Number
ValueCountFrequency (%)
2 128899
23.9%
1 89287
16.6%
5 88250
16.4%
0 46304
 
8.6%
3 43086
 
8.0%
4 38288
 
7.1%
7 36560
 
6.8%
8 34147
 
6.3%
6 18951
 
3.5%
9 15628
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 29792
100.0%
Lowercase Letter
ValueCountFrequency (%)
v 154
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 822313
59.1%
Common 569192
40.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 135289
16.5%
H 105337
12.8%
O 89541
10.9%
B 72954
8.9%
P 56324
 
6.8%
L 50354
 
6.1%
C 44711
 
5.4%
A 42440
 
5.2%
K 39950
 
4.9%
T 37603
 
4.6%
Other values (15) 147810
18.0%
Common
ValueCountFrequency (%)
2 128899
22.6%
1 89287
15.7%
5 88250
15.5%
0 46304
 
8.1%
3 43086
 
7.6%
4 38288
 
6.7%
7 36560
 
6.4%
8 34147
 
6.0%
- 29792
 
5.2%
6 18951
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1391505
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 135289
 
9.7%
2 128899
 
9.3%
H 105337
 
7.6%
O 89541
 
6.4%
1 89287
 
6.4%
5 88250
 
6.3%
B 72954
 
5.2%
P 56324
 
4.0%
L 50354
 
3.6%
0 46304
 
3.3%
Other values (26) 528966
38.0%

Lineitem requires shipping
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size104.9 KiB
True
88938 
False
18353 
ValueCountFrequency (%)
True 88938
82.9%
False 18353
 
17.1%
2024-02-02T12:38:35.308013image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Lineitem taxable
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size104.9 KiB
True
98322 
False
 
8969
ValueCountFrequency (%)
True 98322
91.6%
False 8969
 
8.4%
2024-02-02T12:38:35.350852image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:35.391252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.8918828
Min length7

Characters and Unicode

Total characters954019
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowfulfilled
2nd rowfulfilled
3rd rowfulfilled
4th rowpending
5th rowpending
ValueCountFrequency (%)
fulfilled 101480
94.6%
pending 5799
 
5.4%
restocked 11
 
< 0.1%
partial 1
 
< 0.1%
2024-02-02T12:38:35.503845image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 304441
31.9%
f 202960
21.3%
e 107301
 
11.2%
d 107290
 
11.2%
i 107280
 
11.2%
u 101480
 
10.6%
n 11598
 
1.2%
p 5800
 
0.6%
g 5799
 
0.6%
r 12
 
< 0.1%
Other values (6) 58
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 954019
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 304441
31.9%
f 202960
21.3%
e 107301
 
11.2%
d 107290
 
11.2%
i 107280
 
11.2%
u 101480
 
10.6%
n 11598
 
1.2%
p 5800
 
0.6%
g 5799
 
0.6%
r 12
 
< 0.1%
Other values (6) 58
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 954019
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 304441
31.9%
f 202960
21.3%
e 107301
 
11.2%
d 107290
 
11.2%
i 107280
 
11.2%
u 101480
 
10.6%
n 11598
 
1.2%
p 5800
 
0.6%
g 5799
 
0.6%
r 12
 
< 0.1%
Other values (6) 58
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 954019
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 304441
31.9%
f 202960
21.3%
e 107301
 
11.2%
d 107290
 
11.2%
i 107280
 
11.2%
u 101480
 
10.6%
n 11598
 
1.2%
p 5800
 
0.6%
g 5799
 
0.6%
r 12
 
< 0.1%
Other values (6) 58
 
< 0.1%

Billing Name
Text

MISSING 

Distinct30996
Distinct (%)67.0%
Missing60998
Missing (%)56.9%
Memory size838.3 KiB
2024-02-02T12:38:35.630967image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length58
Median length43
Mean length13.779686
Min length3

Characters and Unicode

Total characters637903
Distinct characters122
Distinct categories13 ?
Distinct scripts5 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22846 ?
Unique (%)49.4%

Sample

1st rowAmanda Dorgan
2nd rowKatherine Gnadinger
3rd rowJessica Wheaton
4th rowSarah Lambert
5th rowNICOLE NELSON
ValueCountFrequency (%)
jessica 617
 
0.7%
sarah 545
 
0.6%
jennifer 531
 
0.6%
emily 476
 
0.5%
ashley 471
 
0.5%
michelle 423
 
0.4%
rachel 387
 
0.4%
elizabeth 379
 
0.4%
lauren 377
 
0.4%
amanda 369
 
0.4%
Other values (23008) 90204
95.2%
2024-02-02T12:38:35.833665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 70390
 
11.0%
e 61097
 
9.6%
50799
 
8.0%
n 46707
 
7.3%
i 43309
 
6.8%
r 38921
 
6.1%
l 34372
 
5.4%
o 27583
 
4.3%
s 23632
 
3.7%
t 19789
 
3.1%
Other values (112) 221304
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 482376
75.6%
Uppercase Letter 103304
 
16.2%
Space Separator 50799
 
8.0%
Dash Punctuation 830
 
0.1%
Other Punctuation 333
 
0.1%
Decimal Number 164
 
< 0.1%
Other Letter 31
 
< 0.1%
Final Punctuation 25
 
< 0.1%
Open Punctuation 17
 
< 0.1%
Close Punctuation 17
 
< 0.1%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 70390
14.6%
e 61097
12.7%
n 46707
9.7%
i 43309
9.0%
r 38921
 
8.1%
l 34372
 
7.1%
o 27583
 
5.7%
s 23632
 
4.9%
t 19789
 
4.1%
h 17454
 
3.6%
Other values (38) 99122
20.5%
Uppercase Letter
ValueCountFrequency (%)
M 9673
 
9.4%
A 9311
 
9.0%
S 8729
 
8.4%
C 7718
 
7.5%
K 6284
 
6.1%
L 6005
 
5.8%
B 5569
 
5.4%
J 5559
 
5.4%
R 5243
 
5.1%
D 4382
 
4.2%
Other values (21) 34831
33.7%
Other Letter
ValueCountFrequency (%)
י 4
12.9%
2
 
6.5%
נ 2
 
6.5%
2
 
6.5%
2
 
6.5%
ט 2
 
6.5%
ג 2
 
6.5%
ק 2
 
6.5%
א 2
 
6.5%
ל 2
 
6.5%
Other values (6) 9
29.0%
Decimal Number
ValueCountFrequency (%)
1 25
15.2%
0 22
13.4%
5 17
10.4%
4 17
10.4%
2 17
10.4%
8 15
9.1%
6 15
9.1%
3 14
8.5%
9 12
7.3%
7 10
 
6.1%
Other Punctuation
ValueCountFrequency (%)
' 149
44.7%
. 111
33.3%
/ 24
 
7.2%
: 22
 
6.6%
, 16
 
4.8%
& 10
 
3.0%
@ 1
 
0.3%
Other Symbol
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Nonspacing Mark
ValueCountFrequency (%)
́ 1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
50799
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 830
100.0%
Final Punctuation
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 585680
91.8%
Common 52190
 
8.2%
Hebrew 20
 
< 0.1%
Han 11
 
< 0.1%
Inherited 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 70390
 
12.0%
e 61097
 
10.4%
n 46707
 
8.0%
i 43309
 
7.4%
r 38921
 
6.6%
l 34372
 
5.9%
o 27583
 
4.7%
s 23632
 
4.0%
t 19789
 
3.4%
h 17454
 
3.0%
Other values (69) 202426
34.6%
Common
ValueCountFrequency (%)
50799
97.3%
- 830
 
1.6%
' 149
 
0.3%
. 111
 
0.2%
1 25
 
< 0.1%
25
 
< 0.1%
/ 24
 
< 0.1%
0 22
 
< 0.1%
: 22
 
< 0.1%
( 17
 
< 0.1%
Other values (15) 166
 
0.3%
Hebrew
ValueCountFrequency (%)
י 4
20.0%
נ 2
10.0%
ט 2
10.0%
ג 2
10.0%
ק 2
10.0%
א 2
10.0%
ל 2
10.0%
ו 2
10.0%
פ 2
10.0%
Han
ValueCountFrequency (%)
2
18.2%
2
18.2%
2
18.2%
2
18.2%
1
9.1%
1
9.1%
1
9.1%
Inherited
ValueCountFrequency (%)
́ 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 637638
> 99.9%
None 203
 
< 0.1%
Punctuation 25
 
< 0.1%
Hebrew 20
 
< 0.1%
CJK 11
 
< 0.1%
Specials 3
 
< 0.1%
Diacriticals 1
 
< 0.1%
VS 1
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 70390
 
11.0%
e 61097
 
9.6%
50799
 
8.0%
n 46707
 
7.3%
i 43309
 
6.8%
r 38921
 
6.1%
l 34372
 
5.4%
o 27583
 
4.3%
s 23632
 
3.7%
t 19789
 
3.1%
Other values (64) 221039
34.7%
None
ValueCountFrequency (%)
é 25
12.3%
í 23
11.3%
ñ 20
9.9%
ó 19
9.4%
á 17
8.4%
ø 16
 
7.9%
ä 12
 
5.9%
ö 11
 
5.4%
ü 10
 
4.9%
ë 8
 
3.9%
Other values (17) 42
20.7%
Punctuation
ValueCountFrequency (%)
25
100.0%
Hebrew
ValueCountFrequency (%)
י 4
20.0%
נ 2
10.0%
ט 2
10.0%
ג 2
10.0%
ק 2
10.0%
א 2
10.0%
ל 2
10.0%
ו 2
10.0%
פ 2
10.0%
Specials
ValueCountFrequency (%)
3
100.0%
CJK
ValueCountFrequency (%)
2
18.2%
2
18.2%
2
18.2%
2
18.2%
1
9.1%
1
9.1%
1
9.1%
Diacriticals
ValueCountFrequency (%)
́ 1
100.0%
VS
ValueCountFrequency (%)
1
100.0%
Misc Symbols
ValueCountFrequency (%)
1
100.0%

Billing Street
Text

MISSING 

Distinct33055
Distinct (%)71.3%
Missing60930
Missing (%)56.8%
Memory size838.3 KiB
2024-02-02T12:38:36.004554image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length109
Median length88
Mean length20.392313
Min length2

Characters and Unicode

Total characters945408
Distinct characters170
Distinct categories13 ?
Distinct scripts6 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25596 ?
Unique (%)55.2%

Sample

1st row4529 185th Pl SW
2nd row7011 Chackbay Ln
3rd row1009 11th Avenue
4th row924 E Juneau Avenue, Unit 502
5th row2 DONALD LANE
ValueCountFrequency (%)
street 5834
 
3.2%
apt 5021
 
2.8%
drive 4679
 
2.6%
st 4175
 
2.3%
avenue 3713
 
2.1%
ave 3495
 
1.9%
road 3263
 
1.8%
dr 3104
 
1.7%
rd 2378
 
1.3%
lane 1827
 
1.0%
Other values (25252) 143605
79.3%
2024-02-02T12:38:36.243450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135531
 
14.3%
e 68158
 
7.2%
t 48442
 
5.1%
r 44164
 
4.7%
a 40174
 
4.2%
1 39289
 
4.2%
o 32568
 
3.4%
n 32019
 
3.4%
2 27475
 
2.9%
i 26882
 
2.8%
Other values (160) 450706
47.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 447381
47.3%
Decimal Number 202837
21.5%
Uppercase Letter 142793
 
15.1%
Space Separator 135541
 
14.3%
Other Punctuation 15650
 
1.7%
Dash Punctuation 1041
 
0.1%
Other Letter 94
 
< 0.1%
Close Punctuation 29
 
< 0.1%
Open Punctuation 29
 
< 0.1%
Final Punctuation 9
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ד 5
 
5.3%
4
 
4.3%
4
 
4.3%
º 4
 
4.3%
ו 3
 
3.2%
י 3
 
3.2%
נ 3
 
3.2%
ג 3
 
3.2%
2
 
2.1%
ح 2
 
2.1%
Other values (47) 61
64.9%
Lowercase Letter
ValueCountFrequency (%)
e 68158
15.2%
t 48442
10.8%
r 44164
9.9%
a 40174
9.0%
o 32568
 
7.3%
n 32019
 
7.2%
i 26882
 
6.0%
l 22585
 
5.0%
d 18204
 
4.1%
s 16728
 
3.7%
Other values (42) 97457
21.8%
Uppercase Letter
ValueCountFrequency (%)
S 18862
13.2%
A 16923
11.9%
R 10811
 
7.6%
D 10724
 
7.5%
C 10038
 
7.0%
W 7746
 
5.4%
E 7366
 
5.2%
L 7239
 
5.1%
P 6772
 
4.7%
N 6765
 
4.7%
Other values (20) 39547
27.7%
Other Punctuation
ValueCountFrequency (%)
, 11567
73.9%
. 2874
 
18.4%
# 913
 
5.8%
/ 235
 
1.5%
' 44
 
0.3%
: 8
 
0.1%
@ 3
 
< 0.1%
& 2
 
< 0.1%
* 1
 
< 0.1%
׳ 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 39289
19.4%
2 27475
13.5%
0 26378
13.0%
3 21053
10.4%
5 18574
9.2%
4 18435
9.1%
6 14731
 
7.3%
7 13099
 
6.5%
8 12656
 
6.2%
9 11147
 
5.5%
Space Separator
ValueCountFrequency (%)
135531
> 99.9%
  10
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1041
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Final Punctuation
ValueCountFrequency (%)
9
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 2
100.0%
Format
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 590178
62.4%
Common 355139
37.6%
Han 40
 
< 0.1%
Hebrew 28
 
< 0.1%
Hangul 17
 
< 0.1%
Arabic 6
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 68158
 
11.5%
t 48442
 
8.2%
r 44164
 
7.5%
a 40174
 
6.8%
o 32568
 
5.5%
n 32019
 
5.4%
i 26882
 
4.6%
l 22585
 
3.8%
S 18862
 
3.2%
d 18204
 
3.1%
Other values (73) 238120
40.3%
Common
ValueCountFrequency (%)
135531
38.2%
1 39289
 
11.1%
2 27475
 
7.7%
0 26378
 
7.4%
3 21053
 
5.9%
5 18574
 
5.2%
4 18435
 
5.2%
6 14731
 
4.1%
7 13099
 
3.7%
8 12656
 
3.6%
Other values (20) 27918
 
7.9%
Han
ValueCountFrequency (%)
2
 
5.0%
2
 
5.0%
2
 
5.0%
2
 
5.0%
2
 
5.0%
广 2
 
5.0%
2
 
5.0%
2
 
5.0%
2
 
5.0%
2
 
5.0%
Other values (20) 20
50.0%
Hebrew
ValueCountFrequency (%)
ד 5
17.9%
ו 3
10.7%
י 3
10.7%
נ 3
10.7%
ג 3
10.7%
ר 2
 
7.1%
ך 2
 
7.1%
ש 2
 
7.1%
ה 2
 
7.1%
ט 1
 
3.6%
Other values (2) 2
 
7.1%
Hangul
ValueCountFrequency (%)
4
23.5%
4
23.5%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Arabic
ValueCountFrequency (%)
ح 2
33.3%
ي 2
33.3%
ن 1
16.7%
ط 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 945039
> 99.9%
None 266
 
< 0.1%
CJK 40
 
< 0.1%
Hebrew 28
 
< 0.1%
Hangul 17
 
< 0.1%
Punctuation 10
 
< 0.1%
Arabic 6
 
< 0.1%
Modifier Letters 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135531
 
14.3%
e 68158
 
7.2%
t 48442
 
5.1%
r 44164
 
4.7%
a 40174
 
4.3%
1 39289
 
4.2%
o 32568
 
3.4%
n 32019
 
3.4%
2 27475
 
2.9%
i 26882
 
2.8%
Other values (67) 450337
47.7%
None
ValueCountFrequency (%)
ß 65
24.4%
é 26
 
9.8%
í 25
 
9.4%
ä 19
 
7.1%
ö 15
 
5.6%
ø 14
 
5.3%
å 13
 
4.9%
ü 12
 
4.5%
  10
 
3.8%
á 9
 
3.4%
Other values (23) 58
21.8%
Punctuation
ValueCountFrequency (%)
9
90.0%
1
 
10.0%
Hebrew
ValueCountFrequency (%)
ד 5
17.9%
ו 3
10.7%
י 3
10.7%
נ 3
10.7%
ג 3
10.7%
ר 2
 
7.1%
ך 2
 
7.1%
ש 2
 
7.1%
ה 2
 
7.1%
ט 1
 
3.6%
Other values (2) 2
 
7.1%
Hangul
ValueCountFrequency (%)
4
23.5%
4
23.5%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
CJK
ValueCountFrequency (%)
2
 
5.0%
2
 
5.0%
2
 
5.0%
2
 
5.0%
2
 
5.0%
广 2
 
5.0%
2
 
5.0%
2
 
5.0%
2
 
5.0%
2
 
5.0%
Other values (20) 20
50.0%
Arabic
ValueCountFrequency (%)
ح 2
33.3%
ي 2
33.3%
ن 1
16.7%
ط 1
16.7%
Modifier Letters
ValueCountFrequency (%)
ʻ 2
100.0%

Billing Address1
Text

MISSING 

Distinct32789
Distinct (%)70.7%
Missing60932
Missing (%)56.8%
Memory size838.3 KiB
2024-02-02T12:38:36.410218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length89
Median length75
Mean length18.480705
Min length1

Characters and Unicode

Total characters856747
Distinct characters162
Distinct categories13 ?
Distinct scripts6 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25236 ?
Unique (%)54.4%

Sample

1st row4529 185th Pl SW
2nd row7011 Chackbay Ln
3rd row1009 11th Avenue
4th row924 E Juneau Avenue
5th row2 DONALD LANE
ValueCountFrequency (%)
street 5797
 
3.6%
drive 4651
 
2.9%
st 4130
 
2.5%
avenue 3701
 
2.3%
ave 3471
 
2.1%
road 3230
 
2.0%
dr 3076
 
1.9%
rd 2353
 
1.4%
lane 1814
 
1.1%
way 1579
 
1.0%
Other values (24004) 128680
79.2%
2024-02-02T12:38:36.639640image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117156
 
13.7%
e 66631
 
7.8%
r 43183
 
5.0%
t 42234
 
4.9%
a 38965
 
4.5%
1 34125
 
4.0%
o 31645
 
3.7%
n 30073
 
3.5%
i 25127
 
2.9%
2 23500
 
2.7%
Other values (152) 404108
47.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 425022
49.6%
Decimal Number 179009
20.9%
Uppercase Letter 130982
 
15.3%
Space Separator 117166
 
13.7%
Other Punctuation 3669
 
0.4%
Dash Punctuation 786
 
0.1%
Other Letter 87
 
< 0.1%
Final Punctuation 8
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ד 5
 
5.7%
4
 
4.6%
4
 
4.6%
ו 3
 
3.4%
נ 3
 
3.4%
י 3
 
3.4%
ג 3
 
3.4%
ש 2
 
2.3%
º 2
 
2.3%
ح 2
 
2.3%
Other values (45) 56
64.4%
Lowercase Letter
ValueCountFrequency (%)
e 66631
15.7%
r 43183
10.2%
t 42234
9.9%
a 38965
9.2%
o 31645
 
7.4%
n 30073
 
7.1%
i 25127
 
5.9%
l 21962
 
5.2%
d 17839
 
4.2%
s 16317
 
3.8%
Other values (41) 91046
21.4%
Uppercase Letter
ValueCountFrequency (%)
S 18304
14.0%
A 12166
 
9.3%
R 10578
 
8.1%
D 10357
 
7.9%
C 9512
 
7.3%
W 7632
 
5.8%
E 6995
 
5.3%
L 6959
 
5.3%
N 6552
 
5.0%
P 6240
 
4.8%
Other values (18) 35687
27.2%
Decimal Number
ValueCountFrequency (%)
1 34125
19.1%
2 23500
13.1%
0 22622
12.6%
3 18138
10.1%
5 16889
9.4%
4 16335
9.1%
6 13238
 
7.4%
7 12068
 
6.7%
8 11672
 
6.5%
9 10422
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 2271
61.9%
, 849
 
23.1%
# 299
 
8.1%
/ 198
 
5.4%
' 43
 
1.2%
: 4
 
0.1%
@ 3
 
0.1%
׳ 1
 
< 0.1%
; 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
117156
> 99.9%
  10
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 786
100.0%
Final Punctuation
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 2
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%
Format
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 556006
64.9%
Common 300655
35.1%
Han 35
 
< 0.1%
Hebrew 28
 
< 0.1%
Hangul 17
 
< 0.1%
Arabic 6
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 66631
 
12.0%
r 43183
 
7.8%
t 42234
 
7.6%
a 38965
 
7.0%
o 31645
 
5.7%
n 30073
 
5.4%
i 25127
 
4.5%
l 21962
 
3.9%
S 18304
 
3.3%
d 17839
 
3.2%
Other values (70) 220043
39.6%
Han
ValueCountFrequency (%)
广 2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (18) 18
51.4%
Common
ValueCountFrequency (%)
117156
39.0%
1 34125
 
11.4%
2 23500
 
7.8%
0 22622
 
7.5%
3 18138
 
6.0%
5 16889
 
5.6%
4 16335
 
5.4%
6 13238
 
4.4%
7 12068
 
4.0%
8 11672
 
3.9%
Other values (17) 14912
 
5.0%
Hebrew
ValueCountFrequency (%)
ד 5
17.9%
ו 3
10.7%
נ 3
10.7%
י 3
10.7%
ג 3
10.7%
ש 2
 
7.1%
ר 2
 
7.1%
ה 2
 
7.1%
ך 2
 
7.1%
׳ 1
 
3.6%
Other values (2) 2
 
7.1%
Hangul
ValueCountFrequency (%)
4
23.5%
4
23.5%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Arabic
ValueCountFrequency (%)
ح 2
33.3%
ي 2
33.3%
ط 1
16.7%
ن 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 856398
> 99.9%
None 252
 
< 0.1%
CJK 35
 
< 0.1%
Hebrew 28
 
< 0.1%
Hangul 17
 
< 0.1%
Punctuation 9
 
< 0.1%
Arabic 6
 
< 0.1%
Modifier Letters 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117156
 
13.7%
e 66631
 
7.8%
r 43183
 
5.0%
t 42234
 
4.9%
a 38965
 
4.5%
1 34125
 
4.0%
o 31645
 
3.7%
n 30073
 
3.5%
i 25127
 
2.9%
2 23500
 
2.7%
Other values (64) 403759
47.1%
None
ValueCountFrequency (%)
ß 65
25.8%
é 25
 
9.9%
í 22
 
8.7%
ä 18
 
7.1%
ö 15
 
6.0%
ø 14
 
5.6%
å 13
 
5.2%
ü 11
 
4.4%
  10
 
4.0%
á 9
 
3.6%
Other values (20) 50
19.8%
Punctuation
ValueCountFrequency (%)
8
88.9%
1
 
11.1%
Hebrew
ValueCountFrequency (%)
ד 5
17.9%
ו 3
10.7%
נ 3
10.7%
י 3
10.7%
ג 3
10.7%
ש 2
 
7.1%
ר 2
 
7.1%
ה 2
 
7.1%
ך 2
 
7.1%
׳ 1
 
3.6%
Other values (2) 2
 
7.1%
Hangul
ValueCountFrequency (%)
4
23.5%
4
23.5%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Arabic
ValueCountFrequency (%)
ح 2
33.3%
ي 2
33.3%
ط 1
16.7%
ن 1
16.7%
CJK
ValueCountFrequency (%)
广 2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (18) 18
51.4%
Modifier Letters
ValueCountFrequency (%)
ʻ 2
100.0%

Billing Address2
Text

MISSING 

Distinct4555
Distinct (%)43.0%
Missing96687
Missing (%)90.1%
Memory size838.3 KiB
2024-02-02T12:38:36.791459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length80
Median length49
Mean length6.3548661
Min length1

Characters and Unicode

Total characters67387
Distinct characters92
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2934 ?
Unique (%)27.7%

Sample

1st rowUnit 502
2nd row2b
3rd row221
4th rowSuite 8258-437
5th rowApt 501
ValueCountFrequency (%)
apt 4096
 
22.5%
unit 1173
 
6.4%
2 330
 
1.8%
1 298
 
1.6%
3 224
 
1.2%
b 224
 
1.2%
a 189
 
1.0%
apartment 158
 
0.9%
ste 152
 
0.8%
4 142
 
0.8%
Other values (3200) 11212
61.6%
2024-02-02T12:38:37.015564image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7761
 
11.5%
t 6208
 
9.2%
1 5164
 
7.7%
A 4742
 
7.0%
p 4135
 
6.1%
2 3975
 
5.9%
0 3756
 
5.6%
3 2915
 
4.3%
4 2100
 
3.1%
n 1942
 
2.9%
Other values (82) 24689
36.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23828
35.4%
Lowercase Letter 22349
33.2%
Uppercase Letter 11781
17.5%
Space Separator 7762
 
11.5%
Other Punctuation 1360
 
2.0%
Dash Punctuation 255
 
0.4%
Open Punctuation 22
 
< 0.1%
Close Punctuation 22
 
< 0.1%
Other Letter 7
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6208
27.8%
p 4135
18.5%
n 1942
 
8.7%
i 1755
 
7.9%
e 1527
 
6.8%
a 1206
 
5.4%
r 981
 
4.4%
o 923
 
4.1%
l 621
 
2.8%
u 440
 
2.0%
Other values (23) 2611
11.7%
Uppercase Letter
ValueCountFrequency (%)
A 4742
40.3%
U 1161
 
9.9%
B 707
 
6.0%
S 558
 
4.7%
T 555
 
4.7%
P 532
 
4.5%
C 526
 
4.5%
E 371
 
3.1%
D 367
 
3.1%
F 318
 
2.7%
Other values (18) 1944
16.5%
Decimal Number
ValueCountFrequency (%)
1 5164
21.7%
2 3975
16.7%
0 3756
15.8%
3 2915
12.2%
4 2100
8.8%
5 1685
 
7.1%
6 1493
 
6.3%
7 1031
 
4.3%
8 984
 
4.1%
9 725
 
3.0%
Other Punctuation
ValueCountFrequency (%)
# 614
45.1%
. 603
44.3%
, 101
 
7.4%
/ 30
 
2.2%
: 4
 
0.3%
' 4
 
0.3%
& 2
 
0.1%
! 1
 
0.1%
* 1
 
0.1%
Other Letter
ValueCountFrequency (%)
º 2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Space Separator
ValueCountFrequency (%)
7761
> 99.9%
  1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 255
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34132
50.7%
Common 33250
49.3%
Han 5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6208
18.2%
A 4742
13.9%
p 4135
12.1%
n 1942
 
5.7%
i 1755
 
5.1%
e 1527
 
4.5%
a 1206
 
3.5%
U 1161
 
3.4%
r 981
 
2.9%
o 923
 
2.7%
Other values (52) 9552
28.0%
Common
ValueCountFrequency (%)
7761
23.3%
1 5164
15.5%
2 3975
12.0%
0 3756
11.3%
3 2915
 
8.8%
4 2100
 
6.3%
5 1685
 
5.1%
6 1493
 
4.5%
7 1031
 
3.1%
8 984
 
3.0%
Other values (15) 2386
 
7.2%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67366
> 99.9%
None 15
 
< 0.1%
CJK 5
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7761
 
11.5%
t 6208
 
9.2%
1 5164
 
7.7%
A 4742
 
7.0%
p 4135
 
6.1%
2 3975
 
5.9%
0 3756
 
5.6%
3 2915
 
4.3%
4 2100
 
3.1%
n 1942
 
2.9%
Other values (65) 24668
36.6%
None
ValueCountFrequency (%)
í 3
20.0%
º 2
13.3%
ã 2
13.3%
ç 1
 
6.7%
ä 1
 
6.7%
Ü 1
 
6.7%
ü 1
 
6.7%
Ä 1
 
6.7%
  1
 
6.7%
ñ 1
 
6.7%
Punctuation
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Billing Company
Text

MISSING 

Distinct614
Distinct (%)65.5%
Missing106353
Missing (%)99.1%
Memory size838.3 KiB
2024-02-02T12:38:37.160745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length62
Median length36
Mean length14.391258
Min length1

Characters and Unicode

Total characters13499
Distinct characters97
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique486 ?
Unique (%)51.8%

Sample

1st rowKailee Rei photography
2nd rowThe Alchemist's Cabin
3rd rowmadii bees closet
4th rowTexas Heat Treating, Inc.
5th rowSocial Work
ValueCountFrequency (%)
corso 118
 
5.6%
llc 55
 
2.6%
the 27
 
1.3%
24
 
1.1%
commerce 19
 
0.9%
of 16
 
0.8%
inc 16
 
0.8%
group 16
 
0.8%
c/o 14
 
0.7%
bridal 13
 
0.6%
Other values (1128) 1800
85.0%
2024-02-02T12:38:37.368616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1230
 
9.1%
e 1195
 
8.9%
o 932
 
6.9%
a 877
 
6.5%
r 757
 
5.6%
i 715
 
5.3%
n 706
 
5.2%
s 630
 
4.7%
t 572
 
4.2%
l 535
 
4.0%
Other values (87) 5350
39.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9308
69.0%
Uppercase Letter 2439
 
18.1%
Space Separator 1230
 
9.1%
Decimal Number 276
 
2.0%
Other Punctuation 184
 
1.4%
Dash Punctuation 31
 
0.2%
Other Letter 15
 
0.1%
Connector Punctuation 5
 
< 0.1%
Final Punctuation 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Other values (3) 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1195
12.8%
o 932
10.0%
a 877
9.4%
r 757
 
8.1%
i 715
 
7.7%
n 706
 
7.6%
s 630
 
6.8%
t 572
 
6.1%
l 535
 
5.7%
c 299
 
3.2%
Other values (24) 2090
22.5%
Uppercase Letter
ValueCountFrequency (%)
C 372
15.3%
L 254
 
10.4%
S 222
 
9.1%
A 144
 
5.9%
M 140
 
5.7%
P 127
 
5.2%
T 113
 
4.6%
D 108
 
4.4%
R 100
 
4.1%
B 97
 
4.0%
Other values (16) 762
31.2%
Other Punctuation
ValueCountFrequency (%)
. 56
30.4%
, 42
22.8%
' 20
 
10.9%
& 17
 
9.2%
/ 16
 
8.7%
@ 15
 
8.2%
: 6
 
3.3%
4
 
2.2%
! 4
 
2.2%
# 3
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 51
18.5%
4 34
12.3%
5 33
12.0%
0 27
9.8%
7 25
9.1%
9 24
8.7%
6 23
8.3%
2 23
8.3%
3 19
 
6.9%
8 17
 
6.2%
Other Letter
ValueCountFrequency (%)
2
13.3%
2
13.3%
2
13.3%
2
13.3%
2
13.3%
2
13.3%
2
13.3%
1
6.7%
Space Separator
ValueCountFrequency (%)
1230
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Final Punctuation
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11747
87.0%
Common 1737
 
12.9%
Han 14
 
0.1%
Hangul 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1195
 
10.2%
o 932
 
7.9%
a 877
 
7.5%
r 757
 
6.4%
i 715
 
6.1%
n 706
 
6.0%
s 630
 
5.4%
t 572
 
4.9%
l 535
 
4.6%
C 372
 
3.2%
Other values (50) 4456
37.9%
Common
ValueCountFrequency (%)
1230
70.8%
. 56
 
3.2%
1 51
 
2.9%
, 42
 
2.4%
4 34
 
2.0%
5 33
 
1.9%
- 31
 
1.8%
0 27
 
1.6%
7 25
 
1.4%
9 24
 
1.4%
Other values (19) 184
 
10.6%
Han
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
Hangul
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13463
99.7%
CJK 14
 
0.1%
None 12
 
0.1%
Punctuation 7
 
0.1%
Letterlike Symbols 2
 
< 0.1%
Hangul 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1230
 
9.1%
e 1195
 
8.9%
o 932
 
6.9%
a 877
 
6.5%
r 757
 
5.6%
i 715
 
5.3%
n 706
 
5.2%
s 630
 
4.7%
t 572
 
4.2%
l 535
 
4.0%
Other values (68) 5314
39.5%
Punctuation
ValueCountFrequency (%)
4
57.1%
3
42.9%
None
ValueCountFrequency (%)
ø 4
33.3%
é 2
16.7%
â 1
 
8.3%
ñ 1
 
8.3%
ó 1
 
8.3%
í 1
 
8.3%
ž 1
 
8.3%
á 1
 
8.3%
Letterlike Symbols
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
Hangul
ValueCountFrequency (%)
1
100.0%

Billing City
Text

MISSING 

Distinct8722
Distinct (%)18.8%
Missing60929
Missing (%)56.8%
Memory size838.3 KiB
2024-02-02T12:38:37.509268image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length40
Median length28
Mean length8.9835426
Min length1

Characters and Unicode

Total characters416495
Distinct characters117
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4098 ?
Unique (%)8.8%

Sample

1st rowLynnwood
2nd rowDallas
3rd rowDorothy
4th rowMilwaukee
5th rowHUNTINGTON
ValueCountFrequency (%)
san 1785
 
2.9%
new 928
 
1.5%
city 906
 
1.5%
beach 706
 
1.2%
york 659
 
1.1%
chicago 604
 
1.0%
park 543
 
0.9%
los 489
 
0.8%
brooklyn 488
 
0.8%
angeles 457
 
0.7%
Other values (5962) 53567
87.6%
2024-02-02T12:38:37.715413image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 35176
 
8.4%
e 34203
 
8.2%
o 30421
 
7.3%
n 29907
 
7.2%
r 23747
 
5.7%
l 23644
 
5.7%
i 23493
 
5.6%
t 19761
 
4.7%
s 17470
 
4.2%
15532
 
3.7%
Other values (107) 163141
39.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 316796
76.1%
Uppercase Letter 83517
 
20.1%
Space Separator 15532
 
3.7%
Other Punctuation 362
 
0.1%
Dash Punctuation 191
 
< 0.1%
Decimal Number 55
 
< 0.1%
Other Letter 32
 
< 0.1%
Final Punctuation 4
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 35176
11.1%
e 34203
10.8%
o 30421
9.6%
n 29907
9.4%
r 23747
 
7.5%
l 23644
 
7.5%
i 23493
 
7.4%
t 19761
 
6.2%
s 17470
 
5.5%
d 9597
 
3.0%
Other values (36) 69377
21.9%
Uppercase Letter
ValueCountFrequency (%)
S 8126
 
9.7%
C 6627
 
7.9%
A 6209
 
7.4%
L 5788
 
6.9%
B 4929
 
5.9%
N 4515
 
5.4%
M 4478
 
5.4%
P 4345
 
5.2%
R 4185
 
5.0%
O 4025
 
4.8%
Other values (20) 30290
36.3%
Other Letter
ValueCountFrequency (%)
י 4
12.5%
נ 4
12.5%
ת 3
 
9.4%
ב 2
 
6.2%
2
 
6.2%
ה 2
 
6.2%
2
 
6.2%
2
 
6.2%
ו 1
 
3.1%
פ 1
 
3.1%
Other values (9) 9
28.1%
Decimal Number
ValueCountFrequency (%)
1 11
20.0%
4 8
14.5%
0 8
14.5%
8 7
12.7%
2 5
9.1%
3 5
9.1%
6 4
 
7.3%
5 3
 
5.5%
9 3
 
5.5%
7 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 257
71.0%
, 58
 
16.0%
' 43
 
11.9%
: 3
 
0.8%
/ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
15532
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 191
100.0%
Final Punctuation
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Format
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 400313
96.1%
Common 16150
 
3.9%
Hebrew 19
 
< 0.1%
Han 9
 
< 0.1%
Hangul 4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 35176
 
8.8%
e 34203
 
8.5%
o 30421
 
7.6%
n 29907
 
7.5%
r 23747
 
5.9%
l 23644
 
5.9%
i 23493
 
5.9%
t 19761
 
4.9%
s 17470
 
4.4%
d 9597
 
2.4%
Other values (66) 152894
38.2%
Common
ValueCountFrequency (%)
15532
96.2%
. 257
 
1.6%
- 191
 
1.2%
, 58
 
0.4%
' 43
 
0.3%
1 11
 
0.1%
4 8
 
< 0.1%
0 8
 
< 0.1%
8 7
 
< 0.1%
2 5
 
< 0.1%
Other values (12) 30
 
0.2%
Hebrew
ValueCountFrequency (%)
י 4
21.1%
נ 4
21.1%
ת 3
15.8%
ב 2
10.5%
ה 2
10.5%
ו 1
 
5.3%
פ 1
 
5.3%
א 1
 
5.3%
ל 1
 
5.3%
Han
ValueCountFrequency (%)
2
22.2%
2
22.2%
2
22.2%
1
11.1%
1
11.1%
1
11.1%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 416293
> 99.9%
None 164
 
< 0.1%
Hebrew 19
 
< 0.1%
CJK 9
 
< 0.1%
Punctuation 5
 
< 0.1%
Hangul 4
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 35176
 
8.4%
e 34203
 
8.2%
o 30421
 
7.3%
n 29907
 
7.2%
r 23747
 
5.7%
l 23644
 
5.7%
i 23493
 
5.6%
t 19761
 
4.7%
s 17470
 
4.2%
15532
 
3.7%
Other values (61) 162939
39.1%
None
ValueCountFrequency (%)
é 51
31.1%
ü 20
 
12.2%
ø 18
 
11.0%
í 10
 
6.1%
è 9
 
5.5%
ö 7
 
4.3%
å 5
 
3.0%
ä 5
 
3.0%
ú 5
 
3.0%
Å 4
 
2.4%
Other values (14) 30
18.3%
Hebrew
ValueCountFrequency (%)
י 4
21.1%
נ 4
21.1%
ת 3
15.8%
ב 2
10.5%
ה 2
10.5%
ו 1
 
5.3%
פ 1
 
5.3%
א 1
 
5.3%
ל 1
 
5.3%
Punctuation
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
CJK
ValueCountFrequency (%)
2
22.2%
2
22.2%
2
22.2%
1
11.1%
1
11.1%
1
11.1%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Modifier Letters
ValueCountFrequency (%)
ʻ 1
100.0%

Billing Zip
Text

MISSING 

Distinct14119
Distinct (%)30.5%
Missing61004
Missing (%)56.9%
Memory size838.3 KiB
2024-02-02T12:38:37.876480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.3195066
Min length3

Characters and Unicode

Total characters292511
Distinct characters41
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6651 ?
Unique (%)14.4%

Sample

1st row'98037
2nd row'75227
3rd row'08317
4th row'53202
5th row'11743
ValueCountFrequency (%)
93401 115
 
0.2%
30309 98
 
0.2%
84790 98
 
0.2%
11201 55
 
0.1%
11374 53
 
0.1%
22201 52
 
0.1%
98507 50
 
0.1%
20002 49
 
0.1%
33445-1436 46
 
0.1%
92626 42
 
0.1%
Other values (14866) 47342
98.6%
2024-02-02T12:38:38.089488image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 40997
14.0%
0 37405
12.8%
1 31083
10.6%
2 27311
9.3%
3 25388
8.7%
4 21756
7.4%
7 20857
7.1%
9 20298
6.9%
5 19931
6.8%
6 18628
6.4%
Other values (31) 28857
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240480
82.2%
Other Punctuation 40997
 
14.0%
Uppercase Letter 5863
 
2.0%
Dash Punctuation 3456
 
1.2%
Space Separator 1713
 
0.6%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 446
 
7.6%
T 407
 
6.9%
V 351
 
6.0%
A 344
 
5.9%
E 321
 
5.5%
H 321
 
5.5%
S 311
 
5.3%
B 310
 
5.3%
N 310
 
5.3%
M 290
 
4.9%
Other values (16) 2452
41.8%
Decimal Number
ValueCountFrequency (%)
0 37405
15.6%
1 31083
12.9%
2 27311
11.4%
3 25388
10.6%
4 21756
9.0%
7 20857
8.7%
9 20298
8.4%
5 19931
8.3%
6 18628
7.7%
8 17823
7.4%
Lowercase Letter
ValueCountFrequency (%)
j 1
50.0%
n 1
50.0%
Other Punctuation
ValueCountFrequency (%)
' 40997
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3456
100.0%
Space Separator
ValueCountFrequency (%)
1713
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 286646
98.0%
Latin 5865
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 446
 
7.6%
T 407
 
6.9%
V 351
 
6.0%
A 344
 
5.9%
E 321
 
5.5%
H 321
 
5.5%
S 311
 
5.3%
B 310
 
5.3%
N 310
 
5.3%
M 290
 
4.9%
Other values (18) 2454
41.8%
Common
ValueCountFrequency (%)
' 40997
14.3%
0 37405
13.0%
1 31083
10.8%
2 27311
9.5%
3 25388
8.9%
4 21756
7.6%
7 20857
7.3%
9 20298
7.1%
5 19931
7.0%
6 18628
6.5%
Other values (3) 22992
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 292511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 40997
14.0%
0 37405
12.8%
1 31083
10.6%
2 27311
9.3%
3 25388
8.7%
4 21756
7.4%
7 20857
7.1%
9 20298
6.9%
5 19931
6.8%
6 18628
6.4%
Other values (31) 28857
9.9%

Billing Province
Text

MISSING 

Distinct181
Distinct (%)0.4%
Missing61597
Missing (%)57.4%
Memory size838.3 KiB
2024-02-02T12:38:38.207868image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.0291286
Min length1

Characters and Unicode

Total characters92719
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)0.1%

Sample

1st rowWA
2nd rowTX
3rd rowNJ
4th rowWI
5th rowNY
ValueCountFrequency (%)
ca 7464
 
16.3%
ny 3433
 
7.5%
tx 3353
 
7.3%
fl 3125
 
6.8%
nj 1697
 
3.7%
il 1694
 
3.7%
pa 1681
 
3.7%
ma 1306
 
2.9%
wa 1298
 
2.8%
va 1286
 
2.8%
Other values (172) 19358
42.4%
2024-02-02T12:38:38.369888image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 16557
17.9%
C 11339
12.2%
N 10307
11.1%
L 5681
 
6.1%
T 5239
 
5.7%
I 4866
 
5.2%
M 4805
 
5.2%
O 4029
 
4.3%
Y 3741
 
4.0%
X 3355
 
3.6%
Other values (25) 22800
24.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 92607
99.9%
Decimal Number 66
 
0.1%
Dash Punctuation 45
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 16557
17.9%
C 11339
12.2%
N 10307
11.1%
L 5681
 
6.1%
T 5239
 
5.7%
I 4866
 
5.3%
M 4805
 
5.2%
O 4029
 
4.4%
Y 3741
 
4.0%
X 3355
 
3.6%
Other values (16) 22688
24.5%
Decimal Number
ValueCountFrequency (%)
0 31
47.0%
1 22
33.3%
3 5
 
7.6%
2 4
 
6.1%
7 2
 
3.0%
4 1
 
1.5%
5 1
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 92607
99.9%
Common 112
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 16557
17.9%
C 11339
12.2%
N 10307
11.1%
L 5681
 
6.1%
T 5239
 
5.7%
I 4866
 
5.3%
M 4805
 
5.2%
O 4029
 
4.4%
Y 3741
 
4.0%
X 3355
 
3.6%
Other values (16) 22688
24.5%
Common
ValueCountFrequency (%)
- 45
40.2%
0 31
27.7%
1 22
19.6%
3 5
 
4.5%
2 4
 
3.6%
7 2
 
1.8%
4 1
 
0.9%
5 1
 
0.9%
1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92719
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 16557
17.9%
C 11339
12.2%
N 10307
11.1%
L 5681
 
6.1%
T 5239
 
5.7%
I 4866
 
5.2%
M 4805
 
5.2%
O 4029
 
4.3%
Y 3741
 
4.0%
X 3355
 
3.6%
Other values (25) 22800
24.6%

Billing Country
Text

MISSING 

Distinct74
Distinct (%)0.2%
Missing60928
Missing (%)56.8%
Memory size838.3 KiB
2024-02-02T12:38:38.447785image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters92726
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 42963
92.7%
ca 1135
 
2.4%
au 676
 
1.5%
gb 549
 
1.2%
de 122
 
0.3%
nz 85
 
0.2%
nl 76
 
0.2%
sg 65
 
0.1%
ch 64
 
0.1%
ie 46
 
0.1%
Other values (64) 582
 
1.3%
2024-02-02T12:38:38.564939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 43652
47.1%
S 43092
46.5%
A 1895
 
2.0%
C 1218
 
1.3%
G 626
 
0.7%
B 608
 
0.7%
E 279
 
0.3%
N 216
 
0.2%
D 164
 
0.2%
I 136
 
0.1%
Other values (16) 840
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 92726
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 43652
47.1%
S 43092
46.5%
A 1895
 
2.0%
C 1218
 
1.3%
G 626
 
0.7%
B 608
 
0.7%
E 279
 
0.3%
N 216
 
0.2%
D 164
 
0.2%
I 136
 
0.1%
Other values (16) 840
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 92726
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 43652
47.1%
S 43092
46.5%
A 1895
 
2.0%
C 1218
 
1.3%
G 626
 
0.7%
B 608
 
0.7%
E 279
 
0.3%
N 216
 
0.2%
D 164
 
0.2%
I 136
 
0.1%
Other values (16) 840
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92726
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 43652
47.1%
S 43092
46.5%
A 1895
 
2.0%
C 1218
 
1.3%
G 626
 
0.7%
B 608
 
0.7%
E 279
 
0.3%
N 216
 
0.2%
D 164
 
0.2%
I 136
 
0.1%
Other values (16) 840
 
0.9%

Billing Phone
Text

MISSING 

Distinct31675
Distinct (%)75.6%
Missing65410
Missing (%)61.0%
Memory size838.3 KiB
2024-02-02T12:38:38.722690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length20
Mean length12.559442
Min length1

Characters and Unicode

Total characters526002
Distinct characters38
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25813 ?
Unique (%)61.6%

Sample

1st row(425) 239-3205
2nd row+18176882853
3rd row+6096029822
4th row(414) 943-1231
5th row+16317218899
ValueCountFrequency (%)
1 2325
 
3.8%
714 199
 
0.3%
415 182
 
0.3%
917 176
 
0.3%
408 171
 
0.3%
808 165
 
0.3%
908 162
 
0.3%
503 155
 
0.3%
805 151
 
0.2%
703 145
 
0.2%
Other values (31576) 58055
93.8%
2024-02-02T12:38:38.951815image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 57716
11.0%
0 45549
8.7%
4 43447
8.3%
3 43435
8.3%
7 43332
8.2%
2 43316
8.2%
5 41171
7.8%
8 40772
7.8%
6 39950
7.6%
9 38174
7.3%
Other values (28) 89140
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 436862
83.1%
Dash Punctuation 20830
 
4.0%
Space Separator 20009
 
3.8%
Math Symbol 16103
 
3.1%
Close Punctuation 14749
 
2.8%
Open Punctuation 14749
 
2.8%
Other Punctuation 2612
 
0.5%
Lowercase Letter 70
 
< 0.1%
Format 8
 
< 0.1%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 31
44.3%
n 29
41.4%
d 2
 
2.9%
t 1
 
1.4%
m 1
 
1.4%
b 1
 
1.4%
r 1
 
1.4%
i 1
 
1.4%
g 1
 
1.4%
e 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 57716
13.2%
0 45549
10.4%
4 43447
9.9%
3 43435
9.9%
7 43332
9.9%
2 43316
9.9%
5 41171
9.4%
8 40772
9.3%
6 39950
9.1%
9 38174
8.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
37.5%
U 3
37.5%
C 1
 
12.5%
R 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
' 2600
99.5%
. 8
 
0.3%
/ 4
 
0.2%
Format
ValueCountFrequency (%)
4
50.0%
3
37.5%
1
 
12.5%
Space Separator
ValueCountFrequency (%)
20008
> 99.9%
  1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 20830
100.0%
Math Symbol
ValueCountFrequency (%)
+ 16103
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14749
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14749
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 525924
> 99.9%
Latin 78
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 57716
11.0%
0 45549
8.7%
4 43447
8.3%
3 43435
8.3%
7 43332
8.2%
2 43316
8.2%
5 41171
7.8%
8 40772
7.8%
6 39950
7.6%
9 38174
7.3%
Other values (13) 89062
16.9%
Latin
ValueCountFrequency (%)
a 31
39.7%
n 29
37.2%
S 3
 
3.8%
U 3
 
3.8%
d 2
 
2.6%
t 1
 
1.3%
C 1
 
1.3%
m 1
 
1.3%
b 1
 
1.3%
r 1
 
1.3%
Other values (5) 5
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 525993
> 99.9%
Punctuation 8
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 57716
11.0%
0 45549
8.7%
4 43447
8.3%
3 43435
8.3%
7 43332
8.2%
2 43316
8.2%
5 41171
7.8%
8 40772
7.8%
6 39950
7.6%
9 38174
7.3%
Other values (24) 89131
16.9%
Punctuation
ValueCountFrequency (%)
4
50.0%
3
37.5%
1
 
12.5%
None
ValueCountFrequency (%)
  1
100.0%

Shipping Name
Text

MISSING 

Distinct30593
Distinct (%)66.5%
Missing61258
Missing (%)57.1%
Memory size838.3 KiB
2024-02-02T12:38:39.108340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length58
Median length42
Mean length13.7812
Min length3

Characters and Unicode

Total characters634390
Distinct characters126
Distinct categories15 ?
Distinct scripts5 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22308 ?
Unique (%)48.5%

Sample

1st rowAmanda Dorgan
2nd rowAndi Baritchi
3rd rowJessica Wheaton
4th rowSarah Lambert
5th rowNICOLE NELSON
ValueCountFrequency (%)
jessica 617
 
0.7%
sarah 552
 
0.6%
jennifer 518
 
0.5%
emily 480
 
0.5%
ashley 471
 
0.5%
michelle 429
 
0.5%
lauren 381
 
0.4%
rachel 380
 
0.4%
elizabeth 378
 
0.4%
amanda 371
 
0.4%
Other values (22890) 89758
95.1%
2024-02-02T12:38:39.330080image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 69863
 
11.0%
e 60915
 
9.6%
50494
 
8.0%
n 46391
 
7.3%
i 43005
 
6.8%
r 38508
 
6.1%
l 34188
 
5.4%
o 27400
 
4.3%
s 23455
 
3.7%
t 19657
 
3.1%
Other values (116) 220514
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 479377
75.6%
Uppercase Letter 102896
 
16.2%
Space Separator 50494
 
8.0%
Dash Punctuation 843
 
0.1%
Other Punctuation 341
 
0.1%
Decimal Number 307
 
< 0.1%
Close Punctuation 33
 
< 0.1%
Open Punctuation 33
 
< 0.1%
Final Punctuation 28
 
< 0.1%
Other Letter 27
 
< 0.1%
Other values (5) 11
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 69863
14.6%
e 60915
12.7%
n 46391
9.7%
i 43005
9.0%
r 38508
 
8.0%
l 34188
 
7.1%
o 27400
 
5.7%
s 23455
 
4.9%
t 19657
 
4.1%
h 17328
 
3.6%
Other values (38) 98667
20.6%
Uppercase Letter
ValueCountFrequency (%)
M 9632
 
9.4%
A 9263
 
9.0%
S 8780
 
8.5%
C 7671
 
7.5%
K 6291
 
6.1%
L 6026
 
5.9%
B 5562
 
5.4%
J 5493
 
5.3%
R 5272
 
5.1%
H 4347
 
4.2%
Other values (21) 34559
33.6%
Other Letter
ValueCountFrequency (%)
י 4
14.8%
ג 2
 
7.4%
ק 2
 
7.4%
א 2
 
7.4%
נ 2
 
7.4%
ט 2
 
7.4%
פ 2
 
7.4%
ו 2
 
7.4%
ל 2
 
7.4%
1
 
3.7%
Other values (6) 6
22.2%
Decimal Number
ValueCountFrequency (%)
1 47
15.3%
3 41
13.4%
2 36
11.7%
4 33
10.7%
5 31
10.1%
8 28
9.1%
0 28
9.1%
6 24
7.8%
9 20
6.5%
7 19
6.2%
Other Punctuation
ValueCountFrequency (%)
' 143
41.9%
. 113
33.1%
/ 26
 
7.6%
: 24
 
7.0%
, 16
 
4.7%
& 14
 
4.1%
# 2
 
0.6%
@ 2
 
0.6%
! 1
 
0.3%
Other Symbol
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Nonspacing Mark
ValueCountFrequency (%)
1
50.0%
́ 1
50.0%
Space Separator
ValueCountFrequency (%)
50494
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 843
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Final Punctuation
ValueCountFrequency (%)
28
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 582273
91.8%
Common 52088
 
8.2%
Hebrew 20
 
< 0.1%
Han 7
 
< 0.1%
Inherited 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 69863
 
12.0%
e 60915
 
10.5%
n 46391
 
8.0%
i 43005
 
7.4%
r 38508
 
6.6%
l 34188
 
5.9%
o 27400
 
4.7%
s 23455
 
4.0%
t 19657
 
3.4%
h 17328
 
3.0%
Other values (69) 201563
34.6%
Common
ValueCountFrequency (%)
50494
96.9%
- 843
 
1.6%
' 143
 
0.3%
. 113
 
0.2%
1 47
 
0.1%
3 41
 
0.1%
2 36
 
0.1%
4 33
 
0.1%
) 33
 
0.1%
( 33
 
0.1%
Other values (19) 272
 
0.5%
Hebrew
ValueCountFrequency (%)
י 4
20.0%
ג 2
10.0%
ק 2
10.0%
א 2
10.0%
נ 2
10.0%
ט 2
10.0%
פ 2
10.0%
ו 2
10.0%
ל 2
10.0%
Han
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Inherited
ValueCountFrequency (%)
1
50.0%
́ 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 634127
> 99.9%
None 202
 
< 0.1%
Punctuation 28
 
< 0.1%
Hebrew 20
 
< 0.1%
CJK 7
 
< 0.1%
Specials 3
 
< 0.1%
VS 1
 
< 0.1%
Misc Symbols 1
 
< 0.1%
Diacriticals 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 69863
 
11.0%
e 60915
 
9.6%
50494
 
8.0%
n 46391
 
7.3%
i 43005
 
6.8%
r 38508
 
6.1%
l 34188
 
5.4%
o 27400
 
4.3%
s 23455
 
3.7%
t 19657
 
3.1%
Other values (68) 220251
34.7%
None
ValueCountFrequency (%)
é 29
14.4%
í 24
11.9%
ó 21
10.4%
á 20
9.9%
ñ 17
8.4%
ø 15
 
7.4%
ö 11
 
5.4%
ü 11
 
5.4%
ä 9
 
4.5%
ë 7
 
3.5%
Other values (17) 38
18.8%
Punctuation
ValueCountFrequency (%)
28
100.0%
Hebrew
ValueCountFrequency (%)
י 4
20.0%
ג 2
10.0%
ק 2
10.0%
א 2
10.0%
נ 2
10.0%
ט 2
10.0%
פ 2
10.0%
ו 2
10.0%
ל 2
10.0%
Specials
ValueCountFrequency (%)
3
100.0%
VS
ValueCountFrequency (%)
1
100.0%
Misc Symbols
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Diacriticals
ValueCountFrequency (%)
́ 1
100.0%

Shipping Street
Text

MISSING 

Distinct32397
Distinct (%)70.4%
Missing61249
Missing (%)57.1%
Memory size838.3 KiB
2024-02-02T12:38:39.496677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length109
Median length88
Mean length20.723883
Min length2

Characters and Unicode

Total characters954169
Distinct characters160
Distinct categories13 ?
Distinct scripts6 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24582 ?
Unique (%)53.4%

Sample

1st row4529 185th Pl SW
2nd row12481 Pleasant Hill Ln
3rd rowPO Box 151
4th row924 E Juneau Avenue, Unit 502
5th row2 DONALD LANE
ValueCountFrequency (%)
street 6062
 
3.3%
apt 5446
 
3.0%
drive 4592
 
2.5%
st 4296
 
2.4%
avenue 3825
 
2.1%
ave 3536
 
1.9%
road 3186
 
1.7%
dr 3033
 
1.7%
rd 2284
 
1.3%
lane 1791
 
1.0%
Other values (24942) 144419
79.1%
2024-02-02T12:38:39.839286image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137271
 
14.4%
e 68717
 
7.2%
t 49966
 
5.2%
r 44198
 
4.6%
1 40287
 
4.2%
a 40240
 
4.2%
o 32310
 
3.4%
n 32228
 
3.4%
2 27940
 
2.9%
i 26956
 
2.8%
Other values (150) 454056
47.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 450070
47.2%
Decimal Number 204943
21.5%
Uppercase Letter 143904
 
15.1%
Space Separator 137291
 
14.4%
Other Punctuation 16700
 
1.8%
Dash Punctuation 1110
 
0.1%
Other Letter 72
 
< 0.1%
Close Punctuation 33
 
< 0.1%
Open Punctuation 32
 
< 0.1%
Final Punctuation 9
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 68717
15.3%
t 49966
11.1%
r 44198
9.8%
a 40240
8.9%
o 32310
 
7.2%
n 32228
 
7.2%
i 26956
 
6.0%
l 22618
 
5.0%
d 17959
 
4.0%
s 16869
 
3.7%
Other values (43) 98009
21.8%
Other Letter
ValueCountFrequency (%)
ד 5
 
6.9%
4
 
5.6%
4
 
5.6%
º 3
 
4.2%
ג 3
 
4.2%
ו 3
 
4.2%
נ 3
 
4.2%
י 3
 
4.2%
ש 2
 
2.8%
ך 2
 
2.8%
Other values (35) 40
55.6%
Uppercase Letter
ValueCountFrequency (%)
S 19275
13.4%
A 17606
12.2%
R 10610
 
7.4%
D 10604
 
7.4%
C 9993
 
6.9%
W 7884
 
5.5%
E 7439
 
5.2%
L 7304
 
5.1%
N 6904
 
4.8%
P 6560
 
4.6%
Other values (22) 39725
27.6%
Other Punctuation
ValueCountFrequency (%)
, 12644
75.7%
. 2703
 
16.2%
# 1032
 
6.2%
/ 251
 
1.5%
' 44
 
0.3%
: 10
 
0.1%
& 8
 
< 0.1%
@ 3
 
< 0.1%
; 2
 
< 0.1%
! 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 40287
19.7%
2 27940
13.6%
0 26711
13.0%
3 21324
10.4%
5 18740
9.1%
4 18506
9.0%
6 14457
 
7.1%
7 13007
 
6.3%
8 12669
 
6.2%
9 11302
 
5.5%
Space Separator
ValueCountFrequency (%)
137271
> 99.9%
  20
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Final Punctuation
ValueCountFrequency (%)
9
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 3
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%
Format
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 593977
62.3%
Common 360122
37.7%
Hebrew 28
 
< 0.1%
Han 19
 
< 0.1%
Hangul 17
 
< 0.1%
Arabic 6
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 68717
 
11.6%
t 49966
 
8.4%
r 44198
 
7.4%
a 40240
 
6.8%
o 32310
 
5.4%
n 32228
 
5.4%
i 26956
 
4.5%
l 22618
 
3.8%
S 19275
 
3.2%
d 17959
 
3.0%
Other values (76) 239510
40.3%
Common
ValueCountFrequency (%)
137271
38.1%
1 40287
 
11.2%
2 27940
 
7.8%
0 26711
 
7.4%
3 21324
 
5.9%
5 18740
 
5.2%
4 18506
 
5.1%
6 14457
 
4.0%
7 13007
 
3.6%
8 12669
 
3.5%
Other values (19) 29210
 
8.1%
Han
ValueCountFrequency (%)
广 2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (8) 8
42.1%
Hebrew
ValueCountFrequency (%)
ד 5
17.9%
ג 3
10.7%
ו 3
10.7%
נ 3
10.7%
י 3
10.7%
ש 2
 
7.1%
ך 2
 
7.1%
ה 2
 
7.1%
ר 2
 
7.1%
׳ 1
 
3.6%
Other values (2) 2
 
7.1%
Hangul
ValueCountFrequency (%)
4
23.5%
4
23.5%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Arabic
ValueCountFrequency (%)
ي 2
33.3%
ح 2
33.3%
ط 1
16.7%
ن 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 953799
> 99.9%
None 287
 
< 0.1%
Hebrew 28
 
< 0.1%
CJK 19
 
< 0.1%
Hangul 17
 
< 0.1%
Punctuation 10
 
< 0.1%
Arabic 6
 
< 0.1%
Modifier Letters 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
137271
 
14.4%
e 68717
 
7.2%
t 49966
 
5.2%
r 44198
 
4.6%
1 40287
 
4.2%
a 40240
 
4.2%
o 32310
 
3.4%
n 32228
 
3.4%
2 27940
 
2.9%
i 26956
 
2.8%
Other values (66) 453686
47.6%
None
ValueCountFrequency (%)
ß 70
24.4%
í 28
 
9.8%
é 25
 
8.7%
  20
 
7.0%
ä 19
 
6.6%
ö 15
 
5.2%
ø 14
 
4.9%
å 12
 
4.2%
ü 12
 
4.2%
á 10
 
3.5%
Other values (26) 62
21.6%
Punctuation
ValueCountFrequency (%)
9
90.0%
1
 
10.0%
Hebrew
ValueCountFrequency (%)
ד 5
17.9%
ג 3
10.7%
ו 3
10.7%
נ 3
10.7%
י 3
10.7%
ש 2
 
7.1%
ך 2
 
7.1%
ה 2
 
7.1%
ר 2
 
7.1%
׳ 1
 
3.6%
Other values (2) 2
 
7.1%
Hangul
ValueCountFrequency (%)
4
23.5%
4
23.5%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Modifier Letters
ValueCountFrequency (%)
ʻ 3
100.0%
Arabic
ValueCountFrequency (%)
ي 2
33.3%
ح 2
33.3%
ط 1
16.7%
ن 1
16.7%
CJK
ValueCountFrequency (%)
广 2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (8) 8
42.1%

Shipping Address1
Text

MISSING 

Distinct32054
Distinct (%)69.6%
Missing61251
Missing (%)57.1%
Memory size838.3 KiB
2024-02-02T12:38:40.003661image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length89
Median length76
Mean length18.57967
Min length1

Characters and Unicode

Total characters855408
Distinct characters156
Distinct categories13 ?
Distinct scripts6 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24115 ?
Unique (%)52.4%

Sample

1st row4529 185th Pl SW
2nd row12481 Pleasant Hill Ln
3rd rowPO Box 151
4th row924 E Juneau Avenue
5th row2 DONALD LANE
ValueCountFrequency (%)
street 6016
 
3.7%
drive 4565
 
2.8%
st 4253
 
2.6%
avenue 3810
 
2.4%
ave 3515
 
2.2%
road 3158
 
2.0%
dr 3006
 
1.9%
rd 2269
 
1.4%
lane 1773
 
1.1%
way 1537
 
0.9%
Other values (23458) 128040
79.1%
2024-02-02T12:38:40.233440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116982
 
13.7%
e 67046
 
7.8%
t 43165
 
5.0%
r 43114
 
5.0%
a 38910
 
4.5%
1 34427
 
4.0%
o 31284
 
3.7%
n 30075
 
3.5%
i 24990
 
2.9%
2 23543
 
2.8%
Other values (146) 401872
47.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 425385
49.7%
Decimal Number 178235
20.8%
Uppercase Letter 130497
 
15.3%
Space Separator 117002
 
13.7%
Other Punctuation 3437
 
0.4%
Dash Punctuation 758
 
0.1%
Other Letter 71
 
< 0.1%
Final Punctuation 8
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 67046
15.8%
t 43165
10.1%
r 43114
10.1%
a 38910
9.1%
o 31284
 
7.4%
n 30075
 
7.1%
i 24990
 
5.9%
l 21897
 
5.1%
d 17585
 
4.1%
s 16414
 
3.9%
Other values (43) 90905
21.4%
Other Letter
ValueCountFrequency (%)
ד 5
 
7.0%
4
 
5.6%
4
 
5.6%
ג 3
 
4.2%
ו 3
 
4.2%
י 3
 
4.2%
נ 3
 
4.2%
ש 2
 
2.8%
ي 2
 
2.8%
ح 2
 
2.8%
Other values (35) 40
56.3%
Uppercase Letter
ValueCountFrequency (%)
S 18652
14.3%
A 12326
 
9.4%
R 10336
 
7.9%
D 10168
 
7.8%
C 9418
 
7.2%
W 7746
 
5.9%
E 7011
 
5.4%
L 6962
 
5.3%
N 6639
 
5.1%
P 5967
 
4.6%
Other values (19) 35272
27.0%
Decimal Number
ValueCountFrequency (%)
1 34427
19.3%
2 23543
13.2%
0 22509
12.6%
3 18063
10.1%
5 16856
9.5%
4 16175
9.1%
6 12930
 
7.3%
7 11789
 
6.6%
8 11521
 
6.5%
9 10422
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 2046
59.5%
, 841
24.5%
# 293
 
8.5%
/ 204
 
5.9%
' 42
 
1.2%
: 5
 
0.1%
@ 3
 
0.1%
; 1
 
< 0.1%
& 1
 
< 0.1%
׳ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
116982
> 99.9%
  20
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 758
100.0%
Final Punctuation
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 3
100.0%
Format
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 555884
65.0%
Common 299454
35.0%
Hebrew 28
 
< 0.1%
Han 19
 
< 0.1%
Hangul 17
 
< 0.1%
Arabic 6
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 67046
 
12.1%
t 43165
 
7.8%
r 43114
 
7.8%
a 38910
 
7.0%
o 31284
 
5.6%
n 30075
 
5.4%
i 24990
 
4.5%
l 21897
 
3.9%
S 18652
 
3.4%
d 17585
 
3.2%
Other values (73) 219166
39.4%
Common
ValueCountFrequency (%)
116982
39.1%
1 34427
 
11.5%
2 23543
 
7.9%
0 22509
 
7.5%
3 18063
 
6.0%
5 16856
 
5.6%
4 16175
 
5.4%
6 12930
 
4.3%
7 11789
 
3.9%
8 11521
 
3.8%
Other values (18) 14659
 
4.9%
Han
ValueCountFrequency (%)
广 2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (8) 8
42.1%
Hebrew
ValueCountFrequency (%)
ד 5
17.9%
ג 3
10.7%
ו 3
10.7%
י 3
10.7%
נ 3
10.7%
ש 2
 
7.1%
ר 2
 
7.1%
ך 2
 
7.1%
ה 2
 
7.1%
׳ 1
 
3.6%
Other values (2) 2
 
7.1%
Hangul
ValueCountFrequency (%)
4
23.5%
4
23.5%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Arabic
ValueCountFrequency (%)
ي 2
33.3%
ح 2
33.3%
ط 1
16.7%
ن 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 855050
> 99.9%
None 276
 
< 0.1%
Hebrew 28
 
< 0.1%
CJK 19
 
< 0.1%
Hangul 17
 
< 0.1%
Punctuation 9
 
< 0.1%
Arabic 6
 
< 0.1%
Modifier Letters 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116982
 
13.7%
e 67046
 
7.8%
t 43165
 
5.0%
r 43114
 
5.0%
a 38910
 
4.6%
1 34427
 
4.0%
o 31284
 
3.7%
n 30075
 
3.5%
i 24990
 
2.9%
2 23543
 
2.8%
Other values (65) 401514
47.0%
None
ValueCountFrequency (%)
ß 70
25.4%
é 25
 
9.1%
í 25
 
9.1%
  20
 
7.2%
ä 18
 
6.5%
ö 15
 
5.4%
ø 14
 
5.1%
å 12
 
4.3%
ü 11
 
4.0%
á 10
 
3.6%
Other values (23) 56
20.3%
Punctuation
ValueCountFrequency (%)
8
88.9%
1
 
11.1%
Hebrew
ValueCountFrequency (%)
ד 5
17.9%
ג 3
10.7%
ו 3
10.7%
י 3
10.7%
נ 3
10.7%
ש 2
 
7.1%
ר 2
 
7.1%
ך 2
 
7.1%
ה 2
 
7.1%
׳ 1
 
3.6%
Other values (2) 2
 
7.1%
Hangul
ValueCountFrequency (%)
4
23.5%
4
23.5%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Modifier Letters
ValueCountFrequency (%)
ʻ 3
100.0%
Arabic
ValueCountFrequency (%)
ي 2
33.3%
ح 2
33.3%
ط 1
16.7%
ن 1
16.7%
CJK
ValueCountFrequency (%)
广 2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (8) 8
42.1%

Shipping Address2
Text

MISSING 

Distinct4944
Distinct (%)42.3%
Missing95615
Missing (%)89.1%
Memory size838.3 KiB
2024-02-02T12:38:40.387458image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length80
Median length50
Mean length6.4529805
Min length1

Characters and Unicode

Total characters75345
Distinct characters86
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3069 ?
Unique (%)26.3%

Sample

1st rowUnit 502
2nd row2b
3rd rowApt 322
4th rowUnit #208
5th row221
ValueCountFrequency (%)
apt 4482
 
22.3%
unit 1276
 
6.4%
2 368
 
1.8%
1 328
 
1.6%
3 253
 
1.3%
b 242
 
1.2%
a 224
 
1.1%
apartment 197
 
1.0%
suite 168
 
0.8%
4 151
 
0.8%
Other values (3496) 12386
61.7%
2024-02-02T12:38:40.614877image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8603
 
11.4%
t 6801
 
9.0%
1 5860
 
7.8%
A 5265
 
7.0%
p 4553
 
6.0%
2 4397
 
5.8%
0 4202
 
5.6%
3 3261
 
4.3%
4 2331
 
3.1%
n 2149
 
2.9%
Other values (76) 27923
37.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26708
35.4%
Lowercase Letter 24675
32.7%
Uppercase Letter 13377
17.8%
Space Separator 8604
 
11.4%
Other Punctuation 1572
 
2.1%
Dash Punctuation 352
 
0.5%
Close Punctuation 28
 
< 0.1%
Open Punctuation 27
 
< 0.1%
Other Letter 1
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6801
27.6%
p 4553
18.5%
n 2149
 
8.7%
i 1966
 
8.0%
e 1671
 
6.8%
a 1327
 
5.4%
r 1084
 
4.4%
o 1026
 
4.2%
l 719
 
2.9%
u 516
 
2.1%
Other values (21) 2863
11.6%
Uppercase Letter
ValueCountFrequency (%)
A 5265
39.4%
U 1290
 
9.6%
B 823
 
6.2%
T 637
 
4.8%
S 623
 
4.7%
P 593
 
4.4%
C 575
 
4.3%
D 436
 
3.3%
E 428
 
3.2%
F 368
 
2.8%
Other values (19) 2339
17.5%
Decimal Number
ValueCountFrequency (%)
1 5860
21.9%
2 4397
16.5%
0 4202
15.7%
3 3261
12.2%
4 2331
 
8.7%
5 1884
 
7.1%
6 1527
 
5.7%
7 1218
 
4.6%
8 1148
 
4.3%
9 880
 
3.3%
Other Punctuation
ValueCountFrequency (%)
# 739
47.0%
. 657
41.8%
, 114
 
7.3%
/ 41
 
2.6%
& 7
 
0.4%
' 6
 
0.4%
: 5
 
0.3%
! 2
 
0.1%
; 1
 
0.1%
Space Separator
ValueCountFrequency (%)
8603
> 99.9%
  1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 352
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Other Letter
ValueCountFrequency (%)
º 1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38053
50.5%
Common 37292
49.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6801
17.9%
A 5265
13.8%
p 4553
12.0%
n 2149
 
5.6%
i 1966
 
5.2%
e 1671
 
4.4%
a 1327
 
3.5%
U 1290
 
3.4%
r 1084
 
2.8%
o 1026
 
2.7%
Other values (51) 10921
28.7%
Common
ValueCountFrequency (%)
8603
23.1%
1 5860
15.7%
2 4397
11.8%
0 4202
11.3%
3 3261
 
8.7%
4 2331
 
6.3%
5 1884
 
5.1%
6 1527
 
4.1%
7 1218
 
3.3%
8 1148
 
3.1%
Other values (15) 2861
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75332
> 99.9%
None 12
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8603
 
11.4%
t 6801
 
9.0%
1 5860
 
7.8%
A 5265
 
7.0%
p 4553
 
6.0%
2 4397
 
5.8%
0 4202
 
5.6%
3 3261
 
4.3%
4 2331
 
3.1%
n 2149
 
2.9%
Other values (65) 27910
37.0%
None
ValueCountFrequency (%)
í 3
25.0%
Ü 1
 
8.3%
Ä 1
 
8.3%
  1
 
8.3%
ü 1
 
8.3%
ä 1
 
8.3%
Í 1
 
8.3%
º 1
 
8.3%
ñ 1
 
8.3%
î 1
 
8.3%
Punctuation
ValueCountFrequency (%)
1
100.0%

Shipping Company
Text

MISSING 

Distinct723
Distinct (%)73.6%
Missing106309
Missing (%)99.1%
Memory size838.3 KiB
2024-02-02T12:38:40.733460image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length71
Median length38
Mean length15.849287
Min length1

Characters and Unicode

Total characters15564
Distinct characters100
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique578 ?
Unique (%)58.9%

Sample

1st rowMCA
2nd rowPod 51 Hotel
3rd rowKailee Rei photography
4th rowThe Alchemist's Cabin
5th rowmadii bees closet
ValueCountFrequency (%)
llc 37
 
1.5%
c/o 30
 
1.2%
30
 
1.2%
the 26
 
1.1%
inc 22
 
0.9%
vcu 18
 
0.7%
group 17
 
0.7%
home 15
 
0.6%
of 14
 
0.6%
bridal 12
 
0.5%
Other values (1336) 2194
90.8%
2024-02-02T12:38:40.919750image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1483
 
9.5%
e 1382
 
8.9%
a 1083
 
7.0%
o 878
 
5.6%
n 853
 
5.5%
i 825
 
5.3%
r 813
 
5.2%
t 757
 
4.9%
l 644
 
4.1%
s 618
 
4.0%
Other values (90) 6228
40.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10678
68.6%
Uppercase Letter 2843
 
18.3%
Space Separator 1483
 
9.5%
Decimal Number 271
 
1.7%
Other Punctuation 215
 
1.4%
Dash Punctuation 40
 
0.3%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%
Other Letter 8
 
0.1%
Connector Punctuation 5
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1382
12.9%
a 1083
10.1%
o 878
 
8.2%
n 853
 
8.0%
i 825
 
7.7%
r 813
 
7.6%
t 757
 
7.1%
l 644
 
6.0%
s 618
 
5.8%
c 358
 
3.4%
Other values (26) 2467
23.1%
Uppercase Letter
ValueCountFrequency (%)
C 317
 
11.2%
S 281
 
9.9%
L 221
 
7.8%
A 184
 
6.5%
M 174
 
6.1%
P 148
 
5.2%
T 141
 
5.0%
D 126
 
4.4%
R 123
 
4.3%
B 121
 
4.3%
Other values (17) 1007
35.4%
Other Punctuation
ValueCountFrequency (%)
. 56
26.0%
, 44
20.5%
/ 37
17.2%
' 23
10.7%
& 18
 
8.4%
@ 14
 
6.5%
: 11
 
5.1%
! 4
 
1.9%
4
 
1.9%
# 3
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 48
17.7%
5 35
12.9%
0 28
10.3%
9 27
10.0%
7 25
9.2%
2 25
9.2%
6 23
8.5%
4 23
8.5%
3 21
7.7%
8 16
 
5.9%
Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Space Separator
ValueCountFrequency (%)
1483
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13521
86.9%
Common 2035
 
13.1%
Han 7
 
< 0.1%
Hangul 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1382
 
10.2%
a 1083
 
8.0%
o 878
 
6.5%
n 853
 
6.3%
i 825
 
6.1%
r 813
 
6.0%
t 757
 
5.6%
l 644
 
4.8%
s 618
 
4.6%
c 358
 
2.6%
Other values (53) 5310
39.3%
Common
ValueCountFrequency (%)
1483
72.9%
. 56
 
2.8%
1 48
 
2.4%
, 44
 
2.2%
- 40
 
2.0%
/ 37
 
1.8%
5 35
 
1.7%
0 28
 
1.4%
9 27
 
1.3%
7 25
 
1.2%
Other values (19) 212
 
10.4%
Han
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Hangul
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15533
99.8%
None 16
 
0.1%
CJK 7
 
< 0.1%
Punctuation 6
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
Hangul 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1483
 
9.5%
e 1382
 
8.9%
a 1083
 
7.0%
o 878
 
5.7%
n 853
 
5.5%
i 825
 
5.3%
r 813
 
5.2%
t 757
 
4.9%
l 644
 
4.1%
s 618
 
4.0%
Other values (68) 6197
39.9%
None
ValueCountFrequency (%)
ø 5
31.2%
é 2
 
12.5%
ž 1
 
6.2%
í 1
 
6.2%
å 1
 
6.2%
Ø 1
 
6.2%
ó 1
 
6.2%
ñ 1
 
6.2%
è 1
 
6.2%
â 1
 
6.2%
Punctuation
ValueCountFrequency (%)
4
66.7%
2
33.3%
CJK
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Hangul
ValueCountFrequency (%)
1
100.0%

Shipping City
Text

MISSING 

Distinct8397
Distinct (%)18.2%
Missing61248
Missing (%)57.1%
Memory size838.3 KiB
2024-02-02T12:38:41.055759image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length40
Median length30
Mean length8.9796712
Min length2

Characters and Unicode

Total characters413451
Distinct characters109
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3843 ?
Unique (%)8.3%

Sample

1st rowLynnwood
2nd rowFrisco
3rd rowDorothy
4th rowMilwaukee
5th rowHUNTINGTON
ValueCountFrequency (%)
san 1728
 
2.8%
new 1008
 
1.7%
city 903
 
1.5%
beach 728
 
1.2%
york 728
 
1.2%
chicago 649
 
1.1%
angeles 535
 
0.9%
los 519
 
0.9%
park 513
 
0.8%
brooklyn 495
 
0.8%
Other values (5722) 52923
87.1%
2024-02-02T12:38:41.259147image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 34840
 
8.4%
e 34044
 
8.2%
o 30272
 
7.3%
n 29628
 
7.2%
l 23551
 
5.7%
r 23547
 
5.7%
i 23275
 
5.6%
t 19695
 
4.8%
s 17460
 
4.2%
15440
 
3.7%
Other values (99) 161699
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 314616
76.1%
Uppercase Letter 82747
 
20.0%
Space Separator 15440
 
3.7%
Other Punctuation 377
 
0.1%
Dash Punctuation 200
 
< 0.1%
Decimal Number 42
 
< 0.1%
Other Letter 19
 
< 0.1%
Final Punctuation 4
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 34840
11.1%
e 34044
10.8%
o 30272
9.6%
n 29628
9.4%
l 23551
 
7.5%
r 23547
 
7.5%
i 23275
 
7.4%
t 19695
 
6.3%
s 17460
 
5.5%
d 9522
 
3.0%
Other values (37) 68782
21.9%
Uppercase Letter
ValueCountFrequency (%)
S 7912
 
9.6%
C 6543
 
7.9%
A 6211
 
7.5%
L 5762
 
7.0%
B 4916
 
5.9%
N 4573
 
5.5%
M 4456
 
5.4%
P 4384
 
5.3%
R 4089
 
4.9%
O 3949
 
4.8%
Other values (21) 29952
36.2%
Decimal Number
ValueCountFrequency (%)
0 8
19.0%
1 8
19.0%
4 6
14.3%
8 6
14.3%
3 5
11.9%
2 4
9.5%
5 2
 
4.8%
7 1
 
2.4%
9 1
 
2.4%
6 1
 
2.4%
Other Letter
ValueCountFrequency (%)
נ 4
21.1%
י 4
21.1%
ת 3
15.8%
ב 2
10.5%
ה 2
10.5%
פ 1
 
5.3%
א 1
 
5.3%
ל 1
 
5.3%
ו 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 276
73.2%
, 54
 
14.3%
' 43
 
11.4%
: 3
 
0.8%
/ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
15440
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%
Final Punctuation
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Format
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 397363
96.1%
Common 16069
 
3.9%
Hebrew 19
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 34840
 
8.8%
e 34044
 
8.6%
o 30272
 
7.6%
n 29628
 
7.5%
l 23551
 
5.9%
r 23547
 
5.9%
i 23275
 
5.9%
t 19695
 
5.0%
s 17460
 
4.4%
d 9522
 
2.4%
Other values (68) 151529
38.1%
Common
ValueCountFrequency (%)
15440
96.1%
. 276
 
1.7%
- 200
 
1.2%
, 54
 
0.3%
' 43
 
0.3%
0 8
 
< 0.1%
1 8
 
< 0.1%
4 6
 
< 0.1%
8 6
 
< 0.1%
3 5
 
< 0.1%
Other values (12) 23
 
0.1%
Hebrew
ValueCountFrequency (%)
נ 4
21.1%
י 4
21.1%
ת 3
15.8%
ב 2
10.5%
ה 2
10.5%
פ 1
 
5.3%
א 1
 
5.3%
ל 1
 
5.3%
ו 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 413269
> 99.9%
None 157
 
< 0.1%
Hebrew 19
 
< 0.1%
Punctuation 5
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 34840
 
8.4%
e 34044
 
8.2%
o 30272
 
7.3%
n 29628
 
7.2%
l 23551
 
5.7%
r 23547
 
5.7%
i 23275
 
5.6%
t 19695
 
4.8%
s 17460
 
4.2%
15440
 
3.7%
Other values (61) 161517
39.1%
None
ValueCountFrequency (%)
é 40
25.5%
ü 18
11.5%
ø 17
10.8%
è 10
 
6.4%
í 10
 
6.4%
ö 8
 
5.1%
ó 8
 
5.1%
å 5
 
3.2%
ú 5
 
3.2%
ä 5
 
3.2%
Other values (16) 31
19.7%
Punctuation
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Hebrew
ValueCountFrequency (%)
נ 4
21.1%
י 4
21.1%
ת 3
15.8%
ב 2
10.5%
ה 2
10.5%
פ 1
 
5.3%
א 1
 
5.3%
ל 1
 
5.3%
ו 1
 
5.3%
Modifier Letters
ValueCountFrequency (%)
ʻ 1
100.0%

Shipping Zip
Text

MISSING 

Distinct13547
Distinct (%)29.5%
Missing61301
Missing (%)57.1%
Memory size838.3 KiB
2024-02-02T12:38:41.410064image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.3024788
Min length3

Characters and Unicode

Total characters289851
Distinct characters41
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6149 ?
Unique (%)13.4%

Sample

1st row'98037
2nd row'75033
3rd row'08317
4th row'53202
5th row'11743
ValueCountFrequency (%)
93401 114
 
0.2%
30309 97
 
0.2%
98363 66
 
0.1%
22201 57
 
0.1%
11201 57
 
0.1%
20002 49
 
0.1%
60614 47
 
0.1%
11374 46
 
0.1%
92626 46
 
0.1%
11101 46
 
0.1%
Other values (14241) 46855
98.7%
2024-02-02T12:38:41.617067image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 41117
14.2%
0 37409
12.9%
1 30959
10.7%
2 27273
9.4%
3 25395
8.8%
4 21472
7.4%
7 20587
7.1%
9 20045
6.9%
5 19625
6.8%
6 18512
6.4%
Other values (31) 27457
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 238896
82.4%
Other Punctuation 41117
 
14.2%
Uppercase Letter 5052
 
1.7%
Dash Punctuation 3294
 
1.1%
Space Separator 1490
 
0.5%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 397
 
7.9%
T 361
 
7.1%
A 292
 
5.8%
V 287
 
5.7%
H 281
 
5.6%
E 277
 
5.5%
B 271
 
5.4%
N 265
 
5.2%
S 263
 
5.2%
P 241
 
4.8%
Other values (16) 2117
41.9%
Decimal Number
ValueCountFrequency (%)
0 37409
15.7%
1 30959
13.0%
2 27273
11.4%
3 25395
10.6%
4 21472
9.0%
7 20587
8.6%
9 20045
8.4%
5 19625
8.2%
6 18512
7.7%
8 17619
7.4%
Lowercase Letter
ValueCountFrequency (%)
j 1
50.0%
n 1
50.0%
Other Punctuation
ValueCountFrequency (%)
' 41117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3294
100.0%
Space Separator
ValueCountFrequency (%)
1490
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 284797
98.3%
Latin 5054
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 397
 
7.9%
T 361
 
7.1%
A 292
 
5.8%
V 287
 
5.7%
H 281
 
5.6%
E 277
 
5.5%
B 271
 
5.4%
N 265
 
5.2%
S 263
 
5.2%
P 241
 
4.8%
Other values (18) 2119
41.9%
Common
ValueCountFrequency (%)
' 41117
14.4%
0 37409
13.1%
1 30959
10.9%
2 27273
9.6%
3 25395
8.9%
4 21472
7.5%
7 20587
7.2%
9 20045
7.0%
5 19625
6.9%
6 18512
6.5%
Other values (3) 22403
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 289851
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 41117
14.2%
0 37409
12.9%
1 30959
10.7%
2 27273
9.4%
3 25395
8.8%
4 21472
7.4%
7 20587
7.1%
9 20045
6.9%
5 19625
6.8%
6 18512
6.4%
Other values (31) 27457
9.5%

Shipping Province
Text

MISSING 

Distinct164
Distinct (%)0.4%
Missing61866
Missing (%)57.7%
Memory size838.3 KiB
2024-02-02T12:38:41.732341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.0265493
Min length1

Characters and Unicode

Total characters92056
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)0.1%

Sample

1st rowWA
2nd rowTX
3rd rowNJ
4th rowWI
5th rowNY
ValueCountFrequency (%)
ca 7372
 
16.2%
ny 3491
 
7.7%
tx 3296
 
7.3%
fl 3153
 
6.9%
il 1699
 
3.7%
pa 1679
 
3.7%
nj 1670
 
3.7%
ma 1333
 
2.9%
wa 1322
 
2.9%
va 1280
 
2.8%
Other values (155) 19131
42.1%
2024-02-02T12:38:41.894205image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 16541
18.0%
C 11205
12.2%
N 10223
11.1%
L 5704
 
6.2%
T 5076
 
5.5%
I 4852
 
5.3%
M 4846
 
5.3%
O 4000
 
4.3%
Y 3788
 
4.1%
X 3298
 
3.6%
Other values (25) 22523
24.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 91985
99.9%
Decimal Number 42
 
< 0.1%
Dash Punctuation 28
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 16541
18.0%
C 11205
12.2%
N 10223
11.1%
L 5704
 
6.2%
T 5076
 
5.5%
I 4852
 
5.3%
M 4846
 
5.3%
O 4000
 
4.3%
Y 3788
 
4.1%
X 3298
 
3.6%
Other values (16) 22452
24.4%
Decimal Number
ValueCountFrequency (%)
1 20
47.6%
0 9
21.4%
3 5
 
11.9%
2 3
 
7.1%
7 2
 
4.8%
4 2
 
4.8%
5 1
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 91985
99.9%
Common 71
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 16541
18.0%
C 11205
12.2%
N 10223
11.1%
L 5704
 
6.2%
T 5076
 
5.5%
I 4852
 
5.3%
M 4846
 
5.3%
O 4000
 
4.3%
Y 3788
 
4.1%
X 3298
 
3.6%
Other values (16) 22452
24.4%
Common
ValueCountFrequency (%)
- 28
39.4%
1 20
28.2%
0 9
 
12.7%
3 5
 
7.0%
2 3
 
4.2%
7 2
 
2.8%
4 2
 
2.8%
5 1
 
1.4%
1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92056
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 16541
18.0%
C 11205
12.2%
N 10223
11.1%
L 5704
 
6.2%
T 5076
 
5.5%
I 4852
 
5.3%
M 4846
 
5.3%
O 4000
 
4.3%
Y 3788
 
4.1%
X 3298
 
3.6%
Other values (25) 22523
24.5%

Shipping Country
Text

MISSING 

Distinct61
Distinct (%)0.1%
Missing61249
Missing (%)57.1%
Memory size838.3 KiB
2024-02-02T12:38:41.969359image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters92084
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 43025
93.4%
ca 959
 
2.1%
au 661
 
1.4%
gb 489
 
1.1%
de 120
 
0.3%
nz 83
 
0.2%
nl 71
 
0.2%
ch 57
 
0.1%
sg 54
 
0.1%
no 42
 
0.1%
Other values (51) 481
 
1.0%
2024-02-02T12:38:42.085263image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 43698
47.5%
S 43139
46.8%
A 1693
 
1.8%
C 1029
 
1.1%
G 553
 
0.6%
B 541
 
0.6%
E 255
 
0.3%
N 202
 
0.2%
D 158
 
0.2%
I 114
 
0.1%
Other values (16) 702
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 92084
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 43698
47.5%
S 43139
46.8%
A 1693
 
1.8%
C 1029
 
1.1%
G 553
 
0.6%
B 541
 
0.6%
E 255
 
0.3%
N 202
 
0.2%
D 158
 
0.2%
I 114
 
0.1%
Other values (16) 702
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 92084
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 43698
47.5%
S 43139
46.8%
A 1693
 
1.8%
C 1029
 
1.1%
G 553
 
0.6%
B 541
 
0.6%
E 255
 
0.3%
N 202
 
0.2%
D 158
 
0.2%
I 114
 
0.1%
Other values (16) 702
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92084
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 43698
47.5%
S 43139
46.8%
A 1693
 
1.8%
C 1029
 
1.1%
G 553
 
0.6%
B 541
 
0.6%
E 255
 
0.3%
N 202
 
0.2%
D 158
 
0.2%
I 114
 
0.1%
Other values (16) 702
 
0.8%

Shipping Phone
Text

MISSING 

Distinct33976
Distinct (%)75.2%
Missing62096
Missing (%)57.9%
Memory size838.3 KiB
2024-02-02T12:38:42.244808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length20
Mean length12.411373
Min length1

Characters and Unicode

Total characters560932
Distinct characters39
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27396 ?
Unique (%)60.6%

Sample

1st row(425) 239-3205
2nd row+18176882853
3rd row+6096029822
4th row(414) 943-1231
5th row+16317218899
ValueCountFrequency (%)
1 2023
 
3.1%
714 200
 
0.3%
415 189
 
0.3%
917 180
 
0.3%
408 178
 
0.3%
808 170
 
0.3%
503 167
 
0.3%
908 155
 
0.2%
805 154
 
0.2%
347 152
 
0.2%
Other values (33758) 61620
94.5%
2024-02-02T12:38:42.471381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 61876
11.0%
0 49277
8.8%
7 46883
8.4%
2 46839
8.4%
4 46580
8.3%
3 46526
8.3%
5 44307
7.9%
8 44172
7.9%
6 43073
7.7%
9 41152
7.3%
Other values (29) 90247
16.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 470685
83.9%
Dash Punctuation 20633
 
3.7%
Space Separator 19996
 
3.6%
Math Symbol 16621
 
3.0%
Close Punctuation 15314
 
2.7%
Open Punctuation 15313
 
2.7%
Other Punctuation 2277
 
0.4%
Lowercase Letter 72
 
< 0.1%
Format 11
 
< 0.1%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 32
44.4%
n 30
41.7%
d 2
 
2.8%
t 1
 
1.4%
o 1
 
1.4%
e 1
 
1.4%
g 1
 
1.4%
r 1
 
1.4%
i 1
 
1.4%
b 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 61876
13.1%
0 49277
10.5%
7 46883
10.0%
2 46839
10.0%
4 46580
9.9%
3 46526
9.9%
5 44307
9.4%
8 44172
9.4%
6 43073
9.2%
9 41152
8.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
37.5%
U 3
37.5%
R 1
 
12.5%
C 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
' 2263
99.4%
. 10
 
0.4%
/ 4
 
0.2%
Format
ValueCountFrequency (%)
6
54.5%
4
36.4%
1
 
9.1%
Space Separator
ValueCountFrequency (%)
19995
> 99.9%
  1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 16620
> 99.9%
= 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 20633
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15314
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15313
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 560852
> 99.9%
Latin 80
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 61876
11.0%
0 49277
8.8%
7 46883
8.4%
2 46839
8.4%
4 46580
8.3%
3 46526
8.3%
5 44307
7.9%
8 44172
7.9%
6 43073
7.7%
9 41152
7.3%
Other values (14) 90167
16.1%
Latin
ValueCountFrequency (%)
a 32
40.0%
n 30
37.5%
S 3
 
3.8%
U 3
 
3.8%
d 2
 
2.5%
t 1
 
1.2%
o 1
 
1.2%
R 1
 
1.2%
e 1
 
1.2%
g 1
 
1.2%
Other values (5) 5
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 560920
> 99.9%
Punctuation 11
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 61876
11.0%
0 49277
8.8%
7 46883
8.4%
2 46839
8.4%
4 46580
8.3%
3 46526
8.3%
5 44307
7.9%
8 44172
7.9%
6 43073
7.7%
9 41152
7.3%
Other values (25) 90235
16.1%
Punctuation
ValueCountFrequency (%)
6
54.5%
4
36.4%
1
 
9.1%
None
ValueCountFrequency (%)
  1
100.0%

Notes
Text

MISSING 

Distinct11215
Distinct (%)91.2%
Missing94999
Missing (%)88.5%
Memory size838.3 KiB
2024-02-02T12:38:42.628593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1101
Median length723
Mean length201.3582
Min length3

Characters and Unicode

Total characters2475095
Distinct characters80
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11111 ?
Unique (%)90.4%

Sample

1st row Return ID 46477192 Initiated @ 2024-01-13 19:19:40 Line items selected: - 10HO21PASPR The Pashionista - Sand Patent Rhinestone/10 – storefront + upsell Exchange 2024-01-19 11:18:04 Exchange processed.
2nd row Return ID 46495450 Initiated @ 2024-01-14 10:19:18 Line items selected: - 65HO23KHCKB4CO The Knee High Boot Coal Knit + Block Heel Kit 4 Coal/6.5 – exchange Exchange 2024-01-25 13:32:11 Exchange processed. Item return @ 2024-01-25 21:32:13
3rd rowEstimated duty and tax $121.04 due upon delivery
4th row Return ID 47453754 Initiated @ 2024-01-30 18:01:10 Line items selected: - 65SP22DOTPBLB3TPB The D'Orsay - Taupe Blush + Block Heel Kit 3 Taupe Blush/6.5 – refund
5th row Return ID 45981383 Initiated @ 2024-01-06 12:11:25 Line items selected: - 95SP22SBSTSS4ST The Slingback - Storm + Stiletto Heel Kit 4 Storm/9.5 – refund Refund requested @ 2024-01-11 16:26:05 $109.88 refunded by Loop. Triggered by Order #75651
ValueCountFrequency (%)
50532
 
13.3%
exchange 15123
 
4.0%
order 14101
 
3.7%
10537
 
2.8%
refund 10335
 
2.7%
return 9374
 
2.5%
heel 8513
 
2.2%
kit 8494
 
2.2%
by 8250
 
2.2%
the 7365
 
1.9%
Other values (39313) 236540
62.4%
2024-02-02T12:38:42.846348image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
329765
 
13.3%
e 211416
 
8.5%
2 104435
 
4.2%
t 100571
 
4.1%
r 93456
 
3.8%
n 80569
 
3.3%
d 79328
 
3.2%
0 75515
 
3.1%
72972
 
2.9%
i 72117
 
2.9%
Other values (70) 1254951
50.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1131884
45.7%
Decimal Number 480653
19.4%
Space Separator 329765
 
13.3%
Uppercase Letter 240088
 
9.7%
Other Punctuation 125973
 
5.1%
Dash Punctuation 76779
 
3.1%
Control 72972
 
2.9%
Math Symbol 8197
 
0.3%
Currency Symbol 7436
 
0.3%
Open Punctuation 674
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 211416
18.7%
t 100571
 
8.9%
r 93456
 
8.3%
n 80569
 
7.1%
d 79328
 
7.0%
i 72117
 
6.4%
a 65318
 
5.8%
o 64083
 
5.7%
s 48150
 
4.3%
l 46662
 
4.1%
Other values (15) 270214
23.9%
Uppercase Letter
ValueCountFrequency (%)
S 24848
10.3%
L 24242
10.1%
H 20702
 
8.6%
T 20021
 
8.3%
O 17947
 
7.5%
B 16908
 
7.0%
I 15356
 
6.4%
R 14632
 
6.1%
C 14439
 
6.0%
K 13135
 
5.5%
Other values (15) 57858
24.1%
Decimal Number
ValueCountFrequency (%)
2 104435
21.7%
0 75515
15.7%
1 67856
14.1%
3 49981
10.4%
5 45130
9.4%
4 38937
 
8.1%
7 26588
 
5.5%
8 26546
 
5.5%
6 23955
 
5.0%
9 21710
 
4.5%
Other Punctuation
ValueCountFrequency (%)
: 48120
38.2%
. 24011
19.1%
* 16972
 
13.5%
@ 16901
 
13.4%
/ 10891
 
8.6%
# 7241
 
5.7%
' 1091
 
0.9%
, 697
 
0.6%
& 48
 
< 0.1%
" 1
 
< 0.1%
Currency Symbol
ValueCountFrequency (%)
$ 7428
99.9%
6
 
0.1%
£ 2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 66242
86.3%
10537
 
13.7%
Space Separator
ValueCountFrequency (%)
329765
100.0%
Control
ValueCountFrequency (%)
72972
100.0%
Math Symbol
ValueCountFrequency (%)
+ 8197
100.0%
Open Punctuation
ValueCountFrequency (%)
( 674
100.0%
Close Punctuation
ValueCountFrequency (%)
) 674
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1371972
55.4%
Common 1103123
44.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 211416
15.4%
t 100571
 
7.3%
r 93456
 
6.8%
n 80569
 
5.9%
d 79328
 
5.8%
i 72117
 
5.3%
a 65318
 
4.8%
o 64083
 
4.7%
s 48150
 
3.5%
l 46662
 
3.4%
Other values (40) 510302
37.2%
Common
ValueCountFrequency (%)
329765
29.9%
2 104435
 
9.5%
0 75515
 
6.8%
72972
 
6.6%
1 67856
 
6.2%
- 66242
 
6.0%
3 49981
 
4.5%
: 48120
 
4.4%
5 45130
 
4.1%
4 38937
 
3.5%
Other values (20) 204170
18.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2464550
99.6%
Punctuation 10537
 
0.4%
Currency Symbols 6
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
329765
 
13.4%
e 211416
 
8.6%
2 104435
 
4.2%
t 100571
 
4.1%
r 93456
 
3.8%
n 80569
 
3.3%
d 79328
 
3.2%
0 75515
 
3.1%
72972
 
3.0%
i 72117
 
2.9%
Other values (67) 1244406
50.5%
Punctuation
ValueCountFrequency (%)
10537
100.0%
Currency Symbols
ValueCountFrequency (%)
6
100.0%
None
ValueCountFrequency (%)
£ 2
100.0%

Note Attributes
Text

MISSING 

Distinct11822
Distinct (%)62.8%
Missing88473
Missing (%)82.5%
Memory size838.3 KiB
2024-02-02T12:38:42.970820image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length291
Median length278
Mean length71.851419
Min length15

Characters and Unicode

Total characters1352100
Distinct characters91
Distinct categories16 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11110 ?
Unique (%)59.0%

Sample

1st rowlc_anon_id: 83a291af-ba4f-4cd6-fec2-2b14713ebb8d exported: fulfilled_by_verte
2nd rowlc_anon_id: 5490dd6f-0b52-45a7-ea72-793a0cded0d8 exported: exported
3rd rowlc_anon_id: d6b67c21-cac3-4bbb-c1bb-64b511954ba8 exported: fulfilled_by_verte
4th rowReferral: Referral Other: Referral Influencer: exported: fulfilled_by_verte
5th rowlc_anon_id: fe1d4348-8697-4c6c-dedd-5640d8c0d98b exported: fulfilled_by_verte
ValueCountFrequency (%)
referral 11411
 
10.1%
lc_anon_id 7673
 
6.8%
estimated 5547
 
4.9%
other 4377
 
3.9%
exported 3835
 
3.4%
loop_gateway 3115
 
2.7%
originating_order_name 3115
 
2.7%
originating_order_id 3115
 
2.7%
stripe 3115
 
2.7%
upsell_amount 3115
 
2.7%
Other values (16917) 64965
57.3%
2024-02-02T12:38:43.160196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 109781
 
8.1%
a 78405
 
5.8%
r 72545
 
5.4%
68698
 
5.1%
i 57063
 
4.2%
l 54627
 
4.0%
t 52630
 
3.9%
n 50540
 
3.7%
: 49322
 
3.6%
d 48797
 
3.6%
Other values (81) 709692
52.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 797879
59.0%
Decimal Number 253500
 
18.7%
Space Separator 68698
 
5.1%
Other Punctuation 61511
 
4.5%
Uppercase Letter 53715
 
4.0%
Connector Punctuation 45411
 
3.4%
Dash Punctuation 31427
 
2.3%
Control 30301
 
2.2%
Currency Symbol 7556
 
0.6%
Close Punctuation 1032
 
0.1%
Other values (6) 1070
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 109781
13.8%
a 78405
9.8%
r 72545
 
9.1%
i 57063
 
7.2%
l 54627
 
6.8%
t 52630
 
6.6%
n 50540
 
6.3%
d 48797
 
6.1%
o 42381
 
5.3%
f 37482
 
4.7%
Other values (18) 193628
24.3%
Uppercase Letter
ValueCountFrequency (%)
R 11626
21.6%
E 6633
12.3%
O 5099
9.5%
T 4834
9.0%
I 4180
 
7.8%
F 3594
 
6.7%
C 3386
 
6.3%
S 2977
 
5.5%
D 2192
 
4.1%
G 1490
 
2.8%
Other values (16) 7704
14.3%
Other Punctuation
ValueCountFrequency (%)
: 49322
80.2%
. 8399
 
13.7%
# 2901
 
4.7%
/ 459
 
0.7%
' 238
 
0.4%
, 119
 
0.2%
! 51
 
0.1%
@ 13
 
< 0.1%
? 3
 
< 0.1%
" 2
 
< 0.1%
Other values (3) 4
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
4 33767
13.3%
0 33643
13.3%
1 24183
9.5%
3 23979
9.5%
5 23827
9.4%
2 23791
9.4%
8 23653
9.3%
6 22557
8.9%
9 22322
8.8%
7 21778
8.6%
Math Symbol
ValueCountFrequency (%)
+ 24
88.9%
< 2
 
7.4%
= 1
 
3.7%
Space Separator
ValueCountFrequency (%)
68698
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 45411
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31427
100.0%
Control
ValueCountFrequency (%)
30301
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 7556
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1032
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1021
100.0%
Final Punctuation
ValueCountFrequency (%)
17
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Nonspacing Mark
ValueCountFrequency (%)
2
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 851594
63.0%
Common 500504
37.0%
Inherited 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 109781
12.9%
a 78405
 
9.2%
r 72545
 
8.5%
i 57063
 
6.7%
l 54627
 
6.4%
t 52630
 
6.2%
n 50540
 
5.9%
d 48797
 
5.7%
o 42381
 
5.0%
f 37482
 
4.4%
Other values (44) 247343
29.0%
Common
ValueCountFrequency (%)
68698
13.7%
: 49322
 
9.9%
_ 45411
 
9.1%
4 33767
 
6.7%
0 33643
 
6.7%
- 31427
 
6.3%
30301
 
6.1%
1 24183
 
4.8%
3 23979
 
4.8%
5 23827
 
4.8%
Other values (26) 135946
27.2%
Inherited
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1352076
> 99.9%
Punctuation 17
 
< 0.1%
None 3
 
< 0.1%
Dingbats 2
 
< 0.1%
VS 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 109781
 
8.1%
a 78405
 
5.8%
r 72545
 
5.4%
68698
 
5.1%
i 57063
 
4.2%
l 54627
 
4.0%
t 52630
 
3.9%
n 50540
 
3.7%
: 49322
 
3.6%
d 48797
 
3.6%
Other values (75) 709668
52.5%
Punctuation
ValueCountFrequency (%)
17
100.0%
Dingbats
ValueCountFrequency (%)
2
100.0%
VS
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
´ 1
33.3%
é 1
33.3%
å 1
33.3%

Cancelled at
Text

MISSING 

Distinct1223
Distinct (%)99.9%
Missing106067
Missing (%)98.9%
Memory size838.3 KiB
2024-02-02T12:38:43.282022image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters30600
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1222 ?
Unique (%)99.8%

Sample

1st row2024-01-17 08:27:45 -0800
2nd row2024-01-15 16:31:19 -0800
3rd row2024-01-19 16:52:05 -0800
4th row2024-01-18 09:49:24 -0800
5th row2024-01-04 10:52:01 -0800
ValueCountFrequency (%)
0700 747
 
20.3%
0800 477
 
13.0%
2023-06-16 23
 
0.6%
2023-11-21 22
 
0.6%
2023-01-30 18
 
0.5%
2023-09-26 14
 
0.4%
2023-08-29 13
 
0.4%
2023-06-07 13
 
0.4%
2023-04-07 12
 
0.3%
2024-01-04 12
 
0.3%
Other values (1602) 2321
63.2%
2024-02-02T12:38:43.454855image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7288
23.8%
2 4327
14.1%
- 3672
12.0%
1 3059
10.0%
2448
 
8.0%
: 2448
 
8.0%
3 1782
 
5.8%
7 1343
 
4.4%
4 1015
 
3.3%
5 1011
 
3.3%
Other values (3) 2207
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22032
72.0%
Dash Punctuation 3672
 
12.0%
Space Separator 2448
 
8.0%
Other Punctuation 2448
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7288
33.1%
2 4327
19.6%
1 3059
13.9%
3 1782
 
8.1%
7 1343
 
6.1%
4 1015
 
4.6%
5 1011
 
4.6%
8 1011
 
4.6%
6 621
 
2.8%
9 575
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 3672
100.0%
Space Separator
ValueCountFrequency (%)
2448
100.0%
Other Punctuation
ValueCountFrequency (%)
: 2448
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7288
23.8%
2 4327
14.1%
- 3672
12.0%
1 3059
10.0%
2448
 
8.0%
: 2448
 
8.0%
3 1782
 
5.8%
7 1343
 
4.4%
4 1015
 
3.3%
5 1011
 
3.3%
Other values (3) 2207
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7288
23.8%
2 4327
14.1%
- 3672
12.0%
1 3059
10.0%
2448
 
8.0%
: 2448
 
8.0%
3 1782
 
5.8%
7 1343
 
4.4%
4 1015
 
3.3%
5 1011
 
3.3%
Other values (3) 2207
 
7.2%

Payment Method
Text

MISSING 

Distinct46
Distinct (%)0.1%
Missing66614
Missing (%)62.1%
Memory size838.3 KiB
2024-02-02T12:38:43.541527image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length56
Median length16
Mean length17.236915
Min length6

Characters and Unicode

Total characters701146
Distinct characters36
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowShopify Payments
2nd rowShopify Payments
3rd rowShopify Payments
4th rowPayPal Express Checkout
5th rowShopify Payments
ValueCountFrequency (%)
shopify 27958
30.2%
payments 27958
30.2%
paypal 6761
 
7.3%
express 6761
 
7.3%
checkout 6761
 
7.3%
pay 3404
 
3.7%
afterpay 1910
 
2.1%
new 1910
 
2.1%
shop 1850
 
2.0%
installments 1800
 
1.9%
Other values (12) 5437
 
5.9%
2024-02-02T12:38:43.672768image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
y 68201
 
9.7%
a 52807
 
7.5%
51833
 
7.4%
e 47309
 
6.7%
s 45130
 
6.4%
P 44675
 
6.4%
t 41346
 
5.9%
p 38688
 
5.5%
o 38173
 
5.4%
h 36828
 
5.3%
Other values (26) 236156
33.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 547022
78.0%
Uppercase Letter 97435
 
13.9%
Space Separator 51833
 
7.4%
Open Punctuation 1910
 
0.3%
Close Punctuation 1910
 
0.3%
Math Symbol 827
 
0.1%
Other Punctuation 209
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
y 68201
12.5%
a 52807
9.7%
e 47309
8.6%
s 45130
 
8.3%
t 41346
 
7.6%
p 38688
 
7.1%
o 38173
 
7.0%
h 36828
 
6.7%
n 34092
 
6.2%
m 31326
 
5.7%
Other values (11) 113122
20.7%
Uppercase Letter
ValueCountFrequency (%)
P 44675
45.9%
S 29808
30.6%
C 7510
 
7.7%
E 6761
 
6.9%
A 3305
 
3.4%
N 1910
 
2.0%
I 1800
 
1.8%
K 758
 
0.8%
G 699
 
0.7%
B 209
 
0.2%
Space Separator
ValueCountFrequency (%)
51833
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1910
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1910
100.0%
Math Symbol
ValueCountFrequency (%)
+ 827
100.0%
Other Punctuation
ValueCountFrequency (%)
, 209
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 644457
91.9%
Common 56689
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
y 68201
 
10.6%
a 52807
 
8.2%
e 47309
 
7.3%
s 45130
 
7.0%
P 44675
 
6.9%
t 41346
 
6.4%
p 38688
 
6.0%
o 38173
 
5.9%
h 36828
 
5.7%
n 34092
 
5.3%
Other values (21) 197208
30.6%
Common
ValueCountFrequency (%)
51833
91.4%
( 1910
 
3.4%
) 1910
 
3.4%
+ 827
 
1.5%
, 209
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 701146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
y 68201
 
9.7%
a 52807
 
7.5%
51833
 
7.4%
e 47309
 
6.7%
s 45130
 
6.4%
P 44675
 
6.4%
t 41346
 
5.9%
p 38688
 
5.5%
o 38173
 
5.4%
h 36828
 
5.3%
Other values (26) 236156
33.7%

Payment Reference
Text

MISSING 

Distinct40675
Distinct (%)100.0%
Missing66616
Missing (%)62.1%
Memory size838.3 KiB
2024-02-02T12:38:43.787631image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length17
Mean length18.657037
Min length8

Characters and Unicode

Total characters758875
Distinct characters64
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40675 ?
Unique (%)100.0%

Sample

1st rowc31677849043142.1
2nd rowrzA7Hrw6aJUPNcsNNmdJNkGRN
3rd rowrV4XQTBerpOSVWdVUkgHXeM9g
4th rowc31733037334726.1
5th rowrtzg5Jpm1kTawKFEgBdDqhcQ9
ValueCountFrequency (%)
c27163116142790.1 1
 
< 0.1%
rk5iirt0osut1ezy8tygnjevv 1
 
< 0.1%
ryvpokv11bw3nkrkda0qnq9of 1
 
< 0.1%
riufxylsexv69o5wwljt5v6fh 1
 
< 0.1%
rza7hrw6ajupncsnnmdjnkgrn 1
 
< 0.1%
rv4xqtberposvwdvukghxem9g 1
 
< 0.1%
c31733037334726.1 1
 
< 0.1%
rtzg5jpm1ktawkfegbddqhcq9 1
 
< 0.1%
c31732657356998.1 1
 
< 0.1%
c31732315750598.1 1
 
< 0.1%
Other values (40665) 40665
> 99.9%
2024-02-02T12:38:43.964584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 74775
 
9.9%
2 70856
 
9.3%
8 49377
 
6.5%
6 48863
 
6.4%
4 46336
 
6.1%
0 46313
 
6.1%
3 45446
 
6.0%
5 43573
 
5.7%
9 43521
 
5.7%
7 42481
 
5.6%
Other values (54) 247334
32.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 511541
67.4%
Lowercase Letter 127344
 
16.8%
Uppercase Letter 87984
 
11.6%
Other Punctuation 32006
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 33458
26.3%
r 11938
 
9.4%
p 5304
 
4.2%
f 3463
 
2.7%
w 3414
 
2.7%
s 3408
 
2.7%
l 3404
 
2.7%
i 3401
 
2.7%
a 3400
 
2.7%
o 3382
 
2.7%
Other values (16) 52772
41.4%
Uppercase Letter
ValueCountFrequency (%)
V 3505
 
4.0%
G 3460
 
3.9%
F 3458
 
3.9%
W 3457
 
3.9%
U 3456
 
3.9%
K 3453
 
3.9%
L 3449
 
3.9%
H 3444
 
3.9%
X 3438
 
3.9%
R 3432
 
3.9%
Other values (16) 53432
60.7%
Decimal Number
ValueCountFrequency (%)
1 74775
14.6%
2 70856
13.9%
8 49377
9.7%
6 48863
9.6%
4 46336
9.1%
0 46313
9.1%
3 45446
8.9%
5 43573
8.5%
9 43521
8.5%
7 42481
8.3%
Other Punctuation
ValueCountFrequency (%)
. 32005
> 99.9%
# 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 543547
71.6%
Latin 215328
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 33458
 
15.5%
r 11938
 
5.5%
p 5304
 
2.5%
V 3505
 
1.6%
f 3463
 
1.6%
G 3460
 
1.6%
F 3458
 
1.6%
W 3457
 
1.6%
U 3456
 
1.6%
K 3453
 
1.6%
Other values (42) 140376
65.2%
Common
ValueCountFrequency (%)
1 74775
13.8%
2 70856
13.0%
8 49377
9.1%
6 48863
9.0%
4 46336
8.5%
0 46313
8.5%
3 45446
8.4%
5 43573
8.0%
9 43521
8.0%
7 42481
7.8%
Other values (2) 32006
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 758875
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 74775
 
9.9%
2 70856
 
9.3%
8 49377
 
6.5%
6 48863
 
6.4%
4 46336
 
6.1%
0 46313
 
6.1%
3 45446
 
6.0%
5 43573
 
5.7%
9 43521
 
5.7%
7 42481
 
5.6%
Other values (54) 247334
32.6%

Refunded Amount
Real number (ℝ)

MISSING  ZEROS 

Distinct3902
Distinct (%)8.4%
Missing60909
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean18.662134
Minimum0
Maximum1654.59
Zeros40995
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:44.044259image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile161.248
Maximum1654.59
Range1654.59
Interquartile range (IQR)0

Descriptive statistics

Standard deviation63.585655
Coefficient of variation (CV)3.4072017
Kurtosis50.035071
Mean18.662134
Median Absolute Deviation (MAD)0
Skewness5.2299565
Sum865587.1
Variance4043.1355
MonotonicityNot monotonic
2024-02-02T12:38:44.099087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 40995
38.2%
180 28
 
< 0.1%
15 24
 
< 0.1%
10 24
 
< 0.1%
8 23
 
< 0.1%
152 20
 
< 0.1%
100 18
 
< 0.1%
30 16
 
< 0.1%
5 15
 
< 0.1%
195 14
 
< 0.1%
Other values (3892) 5205
 
4.9%
(Missing) 60909
56.8%
ValueCountFrequency (%)
0 40995
38.2%
0.01 1
 
< 0.1%
0.1 1
 
< 0.1%
0.47 1
 
< 0.1%
0.51 1
 
< 0.1%
0.55 1
 
< 0.1%
0.73 1
 
< 0.1%
0.86 1
 
< 0.1%
1.09 2
 
< 0.1%
1.1 1
 
< 0.1%
ValueCountFrequency (%)
1654.59 1
< 0.1%
1482.87 1
< 0.1%
1345.58 1
< 0.1%
1232.8 1
< 0.1%
1228 1
< 0.1%
1085 1
< 0.1%
1029 1
< 0.1%
973.23 1
< 0.1%
911.9 1
< 0.1%
885.14 1
< 0.1%

Vendor
Text

Distinct3
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size838.3 KiB
2024-02-02T12:38:44.151801image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length16
Median length16
Mean length14.186863
Min length5

Characters and Unicode

Total characters1522066
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOnward
2nd rowPashion Footwear
3rd rowPashion Footwear
4th rowPashion Footwear
5th rowPashion Footwear
ValueCountFrequency (%)
pashion 89324
45.4%
footwear 89324
45.4%
corso 14896
 
7.6%
onward 3067
 
1.6%
2024-02-02T12:38:44.259043image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 297764
19.6%
a 181715
11.9%
r 107287
 
7.0%
s 104220
 
6.8%
n 92391
 
6.1%
w 92391
 
6.1%
P 89324
 
5.9%
h 89324
 
5.9%
i 89324
 
5.9%
89324
 
5.9%
Other values (6) 289002
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1236131
81.2%
Uppercase Letter 196611
 
12.9%
Space Separator 89324
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 297764
24.1%
a 181715
14.7%
r 107287
 
8.7%
s 104220
 
8.4%
n 92391
 
7.5%
w 92391
 
7.5%
h 89324
 
7.2%
i 89324
 
7.2%
t 89324
 
7.2%
e 89324
 
7.2%
Uppercase Letter
ValueCountFrequency (%)
P 89324
45.4%
F 89324
45.4%
C 14896
 
7.6%
O 3067
 
1.6%
Space Separator
ValueCountFrequency (%)
89324
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1432742
94.1%
Common 89324
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 297764
20.8%
a 181715
12.7%
r 107287
 
7.5%
s 104220
 
7.3%
n 92391
 
6.4%
w 92391
 
6.4%
P 89324
 
6.2%
h 89324
 
6.2%
i 89324
 
6.2%
F 89324
 
6.2%
Other values (5) 199678
13.9%
Common
ValueCountFrequency (%)
89324
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1522066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 297764
19.6%
a 181715
11.9%
r 107287
 
7.0%
s 104220
 
6.8%
n 92391
 
6.1%
w 92391
 
6.1%
P 89324
 
5.9%
h 89324
 
5.9%
i 89324
 
5.9%
89324
 
5.9%
Other values (6) 289002
19.0%

Id
Real number (ℝ)

MISSING 

Distinct46382
Distinct (%)100.0%
Missing60909
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean4.9612224 × 1012
Minimum4.3365281 × 1012
Maximum5.4540597 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:44.329683image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum4.3365281 × 1012
5-th percentile4.4180351 × 1012
Q14.6674646 × 1012
median5.0338501 × 1012
Q35.2345278 × 1012
95-th percentile5.4153796 × 1012
Maximum5.4540597 × 1012
Range1.1175316 × 1012
Interquartile range (IQR)5.6706321 × 1011

Descriptive statistics

Standard deviation3.2807571 × 1011
Coefficient of variation (CV)0.066127999
Kurtosis-1.2290875
Mean4.9612224 × 1012
Median Absolute Deviation (MAD)2.8743249 × 1011
Skewness-0.23176432
Sum2.3011142 × 1017
Variance1.0763367 × 1023
MonotonicityNot monotonic
2024-02-02T12:38:44.500386image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.762922779 × 10121
 
< 0.1%
4.762914685 × 10121
 
< 0.1%
4.762910098 × 10121
 
< 0.1%
4.762902495 × 10121
 
< 0.1%
4.762891518 × 10121
 
< 0.1%
4.762882802 × 10121
 
< 0.1%
4.762871726 × 10121
 
< 0.1%
4.762849051 × 10121
 
< 0.1%
4.762848592 × 10121
 
< 0.1%
4.762843447 × 10121
 
< 0.1%
Other values (46372) 46372
43.2%
(Missing) 60909
56.8%
ValueCountFrequency (%)
4.336528065 × 10121
< 0.1%
4.336940942 × 10121
< 0.1%
4.336957489 × 10121
< 0.1%
4.336973382 × 10121
< 0.1%
4.336998711 × 10121
< 0.1%
4.337074406 × 10121
< 0.1%
4.337076568 × 10121
< 0.1%
4.337326228 × 10121
< 0.1%
4.337343529 × 10121
< 0.1%
4.337361945 × 10121
< 0.1%
ValueCountFrequency (%)
5.454059668 × 10121
< 0.1%
5.454007075 × 10121
< 0.1%
5.453985055 × 10121
< 0.1%
5.453915062 × 10121
< 0.1%
5.453914636 × 10121
< 0.1%
5.45387194 × 10121
< 0.1%
5.453835109 × 10121
< 0.1%
5.453831963 × 10121
< 0.1%
5.453818397 × 10121
< 0.1%
5.45378907 × 10121
< 0.1%

Tags
Text

MISSING 

Distinct3296
Distinct (%)17.0%
Missing87907
Missing (%)81.9%
Memory size838.3 KiB
2024-02-02T12:38:44.565510image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length127
Median length106
Mean length17.948772
Min length2

Characters and Unicode

Total characters347919
Distinct characters65
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3155 ?
Unique (%)16.3%

Sample

1st rowOnward
2nd rowHigh refund, High Volume Customer
3rd rowOnward
4th rowLE:Exchange, Onward
5th rowLE:Exchange, Refund, Zero Refund
ValueCountFrequency (%)
refund 9134
18.6%
high 7718
15.7%
volume 6761
13.8%
customer 6761
13.8%
le:exchange 3110
 
6.3%
onward 3054
 
6.2%
zero 2468
 
5.0%
klickly 2397
 
4.9%
upsell 699
 
1.4%
loop 699
 
1.4%
Other values (3122) 6292
12.8%
2024-02-02T12:38:44.708800image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 30200
 
8.7%
29709
 
8.5%
u 23117
 
6.6%
o 17894
 
5.1%
n 16485
 
4.7%
r 14950
 
4.3%
l 14133
 
4.1%
m 13932
 
4.0%
d 13175
 
3.8%
h 11063
 
3.2%
Other values (55) 163261
46.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 230487
66.2%
Uppercase Letter 52281
 
15.0%
Space Separator 29709
 
8.5%
Other Punctuation 17624
 
5.1%
Decimal Number 16066
 
4.6%
Connector Punctuation 1046
 
0.3%
Dash Punctuation 706
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 30200
13.1%
u 23117
 
10.0%
o 17894
 
7.8%
n 16485
 
7.2%
r 14950
 
6.5%
l 14133
 
6.1%
m 13932
 
6.0%
d 13175
 
5.7%
h 11063
 
4.8%
i 11029
 
4.8%
Other values (15) 64509
28.0%
Uppercase Letter
ValueCountFrequency (%)
C 8309
15.9%
R 8212
15.7%
H 7718
14.8%
V 6761
12.9%
E 6439
12.3%
L 3810
7.3%
O 3160
 
6.0%
K 2637
 
5.0%
Z 2468
 
4.7%
Q 809
 
1.5%
Other values (13) 1958
 
3.7%
Decimal Number
ValueCountFrequency (%)
4 2123
13.2%
3 1923
12.0%
6 1793
11.2%
5 1791
11.1%
2 1640
10.2%
1 1582
9.8%
7 1484
9.2%
0 1295
8.1%
9 1244
7.7%
8 1191
7.4%
Other Punctuation
ValueCountFrequency (%)
, 10913
61.9%
: 3809
 
21.6%
# 2901
 
16.5%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
29709
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1046
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 706
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 282768
81.3%
Common 65151
 
18.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 30200
 
10.7%
u 23117
 
8.2%
o 17894
 
6.3%
n 16485
 
5.8%
r 14950
 
5.3%
l 14133
 
5.0%
m 13932
 
4.9%
d 13175
 
4.7%
h 11063
 
3.9%
i 11029
 
3.9%
Other values (38) 116790
41.3%
Common
ValueCountFrequency (%)
29709
45.6%
, 10913
 
16.8%
: 3809
 
5.8%
# 2901
 
4.5%
4 2123
 
3.3%
3 1923
 
3.0%
6 1793
 
2.8%
5 1791
 
2.7%
2 1640
 
2.5%
1 1582
 
2.4%
Other values (7) 6967
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 347919
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 30200
 
8.7%
29709
 
8.5%
u 23117
 
6.6%
o 17894
 
5.1%
n 16485
 
4.7%
r 14950
 
4.3%
l 14133
 
4.1%
m 13932
 
4.0%
d 13175
 
3.8%
h 11063
 
3.2%
Other values (55) 163261
46.9%

Risk Level
Text

MISSING 

Distinct3
Distinct (%)< 0.1%
Missing60909
Missing (%)56.8%
Memory size838.3 KiB
2024-02-02T12:38:44.765236image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0082144
Min length3

Characters and Unicode

Total characters139527
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLow
2nd rowLow
3rd rowLow
4th rowLow
5th rowLow
ValueCountFrequency (%)
low 46233
99.7%
medium 116
 
0.3%
high 33
 
0.1%
2024-02-02T12:38:44.867456image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
L 46233
33.1%
o 46233
33.1%
w 46233
33.1%
i 149
 
0.1%
M 116
 
0.1%
e 116
 
0.1%
d 116
 
0.1%
u 116
 
0.1%
m 116
 
0.1%
H 33
 
< 0.1%
Other values (2) 66
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 93145
66.8%
Uppercase Letter 46382
33.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 46233
49.6%
w 46233
49.6%
i 149
 
0.2%
e 116
 
0.1%
d 116
 
0.1%
u 116
 
0.1%
m 116
 
0.1%
g 33
 
< 0.1%
h 33
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
L 46233
99.7%
M 116
 
0.3%
H 33
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 139527
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 46233
33.1%
o 46233
33.1%
w 46233
33.1%
i 149
 
0.1%
M 116
 
0.1%
e 116
 
0.1%
d 116
 
0.1%
u 116
 
0.1%
m 116
 
0.1%
H 33
 
< 0.1%
Other values (2) 66
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 139527
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
L 46233
33.1%
o 46233
33.1%
w 46233
33.1%
i 149
 
0.1%
M 116
 
0.1%
e 116
 
0.1%
d 116
 
0.1%
u 116
 
0.1%
m 116
 
0.1%
H 33
 
< 0.1%
Other values (2) 66
 
< 0.1%

Source
Text

MISSING 

Distinct11
Distinct (%)< 0.1%
Missing60909
Missing (%)56.8%
Memory size838.3 KiB
2024-02-02T12:38:44.926392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length19
Median length3
Mean length3.7344013
Min length3

Characters and Unicode

Total characters173209
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowweb
2nd rowweb
3rd rowweb
4th rowweb
5th rowweb
ValueCountFrequency (%)
web 40390
87.1%
1662707 3115
 
6.7%
1424624 1633
 
3.5%
shopify_draft_order 843
 
1.8%
3890849 150
 
0.3%
5698203 98
 
0.2%
2329312 96
 
0.2%
1830279 26
 
0.1%
iphone 21
 
< 0.1%
5179565 9
 
< 0.1%
2024-02-02T12:38:45.039439image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 41254
23.8%
w 40390
23.3%
b 40390
23.3%
6 7970
 
4.6%
2 6794
 
3.9%
7 6266
 
3.6%
4 5050
 
2.9%
1 4881
 
2.8%
0 3389
 
2.0%
r 2529
 
1.5%
Other values (16) 14296
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 135627
78.3%
Decimal Number 35896
 
20.7%
Connector Punctuation 1686
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 41254
30.4%
w 40390
29.8%
b 40390
29.8%
r 2529
 
1.9%
o 1707
 
1.3%
f 1686
 
1.2%
d 1686
 
1.2%
i 864
 
0.6%
p 864
 
0.6%
h 864
 
0.6%
Other values (5) 3393
 
2.5%
Decimal Number
ValueCountFrequency (%)
6 7970
22.2%
2 6794
18.9%
7 6266
17.5%
4 5050
14.1%
1 4881
13.6%
0 3389
9.4%
9 529
 
1.5%
3 466
 
1.3%
8 425
 
1.2%
5 126
 
0.4%
Connector Punctuation
ValueCountFrequency (%)
_ 1686
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 135627
78.3%
Common 37582
 
21.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 41254
30.4%
w 40390
29.8%
b 40390
29.8%
r 2529
 
1.9%
o 1707
 
1.3%
f 1686
 
1.2%
d 1686
 
1.2%
i 864
 
0.6%
p 864
 
0.6%
h 864
 
0.6%
Other values (5) 3393
 
2.5%
Common
ValueCountFrequency (%)
6 7970
21.2%
2 6794
18.1%
7 6266
16.7%
4 5050
13.4%
1 4881
13.0%
0 3389
9.0%
_ 1686
 
4.5%
9 529
 
1.4%
3 466
 
1.2%
8 425
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 173209
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 41254
23.8%
w 40390
23.3%
b 40390
23.3%
6 7970
 
4.6%
2 6794
 
3.9%
7 6266
 
3.6%
4 5050
 
2.9%
1 4881
 
2.8%
0 3389
 
2.0%
r 2529
 
1.5%
Other values (16) 14296
 
8.3%

Lineitem discount
Real number (ℝ)

ZEROS 

Distinct316
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.44573655
Minimum0
Maximum190
Zeros105679
Zeros (%)98.5%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:45.109079image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum190
Range190
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.4922964
Coefficient of variation (CV)12.321844
Kurtosis346.65849
Mean0.44573655
Median Absolute Deviation (MAD)0
Skewness17.057093
Sum47823.52
Variance30.16532
MonotonicityNot monotonic
2024-02-02T12:38:45.166466image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 105679
98.5%
5 137
 
0.1%
1.5 135
 
0.1%
4 133
 
0.1%
30 61
 
0.1%
35 50
 
< 0.1%
10 45
 
< 0.1%
50 38
 
< 0.1%
40 38
 
< 0.1%
20 37
 
< 0.1%
Other values (306) 938
 
0.9%
ValueCountFrequency (%)
0 105679
98.5%
0.09 1
 
< 0.1%
0.11 1
 
< 0.1%
0.25 1
 
< 0.1%
0.8 1
 
< 0.1%
0.9 2
 
< 0.1%
1 13
 
< 0.1%
1.06 1
 
< 0.1%
1.2 5
 
< 0.1%
1.28 1
 
< 0.1%
ValueCountFrequency (%)
190 1
< 0.1%
175 2
< 0.1%
174.07 1
< 0.1%
171 1
< 0.1%
170 1
< 0.1%
165 2
< 0.1%
164.2 1
< 0.1%
160.66 1
< 0.1%
152.51 1
< 0.1%
152 1
< 0.1%

Tax 1 Name
Text

MISSING 

Distinct858
Distinct (%)2.7%
Missing75199
Missing (%)70.1%
Memory size838.3 KiB
2024-02-02T12:38:45.279887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length98
Median length65
Mean length22.342017
Min length6

Characters and Unicode

Total characters717000
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique253 ?
Unique (%)0.8%

Sample

1st rowLynnwood City Tax 4.1%
2nd rowTexas State Tax 0%
3rd rowNew Jersey State Tax 0%
4th rowWisconsin State Tax 0%
5th rowNew York State Tax 0%
ValueCountFrequency (%)
tax 30437
22.9%
state 22260
16.7%
0 10240
 
7.7%
6 6913
 
5.2%
california 6494
 
4.9%
county 4833
 
3.6%
7.25 3734
 
2.8%
city 3002
 
2.3%
new 2428
 
1.8%
florida 2322
 
1.7%
Other values (733) 40282
30.3%
2024-02-02T12:38:45.468084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100853
14.1%
a 90743
 
12.7%
t 59323
 
8.3%
e 38848
 
5.4%
T 33511
 
4.7%
x 32382
 
4.5%
i 32218
 
4.5%
% 32092
 
4.5%
o 28554
 
4.0%
n 25099
 
3.5%
Other values (58) 243377
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 418721
58.4%
Uppercase Letter 103176
 
14.4%
Space Separator 100853
 
14.1%
Decimal Number 51541
 
7.2%
Other Punctuation 42703
 
6.0%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 33511
32.5%
S 24622
23.9%
C 19161
18.6%
M 3422
 
3.3%
F 3295
 
3.2%
N 3095
 
3.0%
A 2518
 
2.4%
Y 1509
 
1.5%
D 1357
 
1.3%
P 1316
 
1.3%
Other values (16) 9370
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
a 90743
21.7%
t 59323
14.2%
e 38848
9.3%
x 32382
 
7.7%
i 32218
 
7.7%
o 28554
 
6.8%
n 25099
 
6.0%
r 20787
 
5.0%
l 18424
 
4.4%
y 11220
 
2.7%
Other values (15) 61123
14.6%
Decimal Number
ValueCountFrequency (%)
0 11826
22.9%
5 9683
18.8%
6 8029
15.6%
2 7222
14.0%
7 6668
12.9%
1 4509
 
8.7%
4 1643
 
3.2%
3 1417
 
2.7%
9 418
 
0.8%
8 126
 
0.2%
Other Punctuation
ValueCountFrequency (%)
% 32092
75.2%
. 10601
 
24.8%
/ 9
 
< 0.1%
' 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
100853
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 521897
72.8%
Common 195103
 
27.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 90743
17.4%
t 59323
11.4%
e 38848
 
7.4%
T 33511
 
6.4%
x 32382
 
6.2%
i 32218
 
6.2%
o 28554
 
5.5%
n 25099
 
4.8%
S 24622
 
4.7%
r 20787
 
4.0%
Other values (41) 135810
26.0%
Common
ValueCountFrequency (%)
100853
51.7%
% 32092
 
16.4%
0 11826
 
6.1%
. 10601
 
5.4%
5 9683
 
5.0%
6 8029
 
4.1%
2 7222
 
3.7%
7 6668
 
3.4%
1 4509
 
2.3%
4 1643
 
0.8%
Other values (7) 1977
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 717000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100853
14.1%
a 90743
 
12.7%
t 59323
 
8.3%
e 38848
 
5.4%
T 33511
 
4.7%
x 32382
 
4.5%
i 32218
 
4.5%
% 32092
 
4.5%
o 28554
 
4.0%
n 25099
 
3.5%
Other values (58) 243377
33.9%

Tax 1 Value
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct2346
Distinct (%)7.3%
Missing75199
Missing (%)70.1%
Infinite0
Infinite (%)0.0%
Mean4.7590315
Minimum0
Maximum128.94
Zeros11708
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:45.545626image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.86
Q38.4
95-th percentile16.1
Maximum128.94
Range128.94
Interquartile range (IQR)8.4

Descriptive statistics

Standard deviation6.5612972
Coefficient of variation (CV)1.3787043
Kurtosis16.736399
Mean4.7590315
Median Absolute Deviation (MAD)1.86
Skewness2.7019671
Sum152726.84
Variance43.050621
MonotonicityNot monotonic
2024-02-02T12:38:45.608784image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11708
 
10.9%
0.27 256
 
0.2%
8.88 237
 
0.2%
9.12 221
 
0.2%
10.8 215
 
0.2%
11.02 165
 
0.2%
11.31 161
 
0.2%
6 153
 
0.1%
10.73 144
 
0.1%
11.4 135
 
0.1%
Other values (2336) 18697
 
17.4%
(Missing) 75199
70.1%
ValueCountFrequency (%)
0 11708
10.9%
0.01 9
 
< 0.1%
0.02 16
 
< 0.1%
0.03 19
 
< 0.1%
0.04 17
 
< 0.1%
0.05 11
 
< 0.1%
0.06 11
 
< 0.1%
0.07 13
 
< 0.1%
0.08 12
 
< 0.1%
0.09 25
 
< 0.1%
ValueCountFrequency (%)
128.94 1
< 0.1%
102.03 1
< 0.1%
96.28 1
< 0.1%
85.41 1
< 0.1%
83.52 1
< 0.1%
81.72 1
< 0.1%
80.95 1
< 0.1%
70.62 1
< 0.1%
68.88 1
< 0.1%
65.7 1
< 0.1%

Tax 2 Name
Text

MISSING 

Distinct843
Distinct (%)4.3%
Missing87548
Missing (%)81.6%
Memory size838.3 KiB
2024-02-02T12:38:45.737451image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length98
Median length60
Mean length23.604265
Min length6

Characters and Unicode

Total characters466019
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique260 ?
Unique (%)1.3%

Sample

1st rowSnohomish County Tax 0%
2nd rowSan Bernardino Co Local Tax Sl 1%
3rd rowDupage County Tax 0%
4th rowSacramento City Tax 1%
5th rowPST 7%
ValueCountFrequency (%)
tax 18927
21.3%
county 8119
 
9.1%
state 5831
 
6.6%
1 4761
 
5.4%
city 2982
 
3.4%
co 2260
 
2.5%
0.5 2224
 
2.5%
local 2022
 
2.3%
sl 1977
 
2.2%
san 1713
 
1.9%
Other values (794) 38172
42.9%
2024-02-02T12:38:45.951782image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69245
 
14.9%
a 46357
 
9.9%
o 28254
 
6.1%
t 28211
 
6.1%
n 21695
 
4.7%
% 19743
 
4.2%
T 19741
 
4.2%
x 19099
 
4.1%
e 18028
 
3.9%
C 16711
 
3.6%
Other values (60) 178935
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 256169
55.0%
Uppercase Letter 70467
 
15.1%
Space Separator 69245
 
14.9%
Decimal Number 38710
 
8.3%
Other Punctuation 31390
 
6.7%
Open Punctuation 19
 
< 0.1%
Close Punctuation 19
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 46357
18.1%
o 28254
11.0%
t 28211
11.0%
n 21695
8.5%
x 19099
7.5%
e 18028
 
7.0%
i 16352
 
6.4%
l 13500
 
5.3%
y 11506
 
4.5%
u 10698
 
4.2%
Other values (16) 42469
16.6%
Uppercase Letter
ValueCountFrequency (%)
T 19741
28.0%
C 16711
23.7%
S 11745
16.7%
L 4380
 
6.2%
O 2332
 
3.3%
A 1817
 
2.6%
D 1734
 
2.5%
F 1585
 
2.2%
M 1297
 
1.8%
W 1120
 
1.6%
Other values (16) 8005
11.4%
Decimal Number
ValueCountFrequency (%)
5 11573
29.9%
1 6915
17.9%
2 4640
12.0%
0 4286
 
11.1%
7 3786
 
9.8%
6 2735
 
7.1%
4 2112
 
5.5%
3 1488
 
3.8%
9 722
 
1.9%
8 453
 
1.2%
Other Punctuation
ValueCountFrequency (%)
% 19743
62.9%
. 11642
37.1%
/ 3
 
< 0.1%
# 1
 
< 0.1%
' 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
69245
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 326636
70.1%
Common 139383
29.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 46357
14.2%
o 28254
 
8.6%
t 28211
 
8.6%
n 21695
 
6.6%
T 19741
 
6.0%
x 19099
 
5.8%
e 18028
 
5.5%
C 16711
 
5.1%
i 16352
 
5.0%
l 13500
 
4.1%
Other values (42) 98688
30.2%
Common
ValueCountFrequency (%)
69245
49.7%
% 19743
 
14.2%
. 11642
 
8.4%
5 11573
 
8.3%
1 6915
 
5.0%
2 4640
 
3.3%
0 4286
 
3.1%
7 3786
 
2.7%
6 2735
 
2.0%
4 2112
 
1.5%
Other values (8) 2706
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 466019
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
69245
 
14.9%
a 46357
 
9.9%
o 28254
 
6.1%
t 28211
 
6.1%
n 21695
 
4.7%
% 19743
 
4.2%
T 19741
 
4.2%
x 19099
 
4.1%
e 18028
 
3.9%
C 16711
 
3.6%
Other values (60) 178935
38.4%

Tax 2 Value
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct1865
Distinct (%)9.4%
Missing87548
Missing (%)81.6%
Infinite0
Infinite (%)0.0%
Mean4.000036
Minimum0
Maximum80.19
Zeros2092
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:46.035553image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.77
median1.95
Q35.76
95-th percentile13.337
Maximum80.19
Range80.19
Interquartile range (IQR)4.99

Descriptive statistics

Standard deviation4.9743452
Coefficient of variation (CV)1.2435751
Kurtosis13.29093
Mean4.000036
Median Absolute Deviation (MAD)1.69
Skewness2.6608058
Sum78972.71
Variance24.74411
MonotonicityNot monotonic
2024-02-02T12:38:46.095541image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2092
 
1.9%
1.48 183
 
0.2%
1.52 170
 
0.2%
1.8 154
 
0.1%
1 142
 
0.1%
0.95 131
 
0.1%
1.9 124
 
0.1%
0.74 121
 
0.1%
0.76 121
 
0.1%
0.78 119
 
0.1%
Other values (1855) 16386
 
15.3%
(Missing) 87548
81.6%
ValueCountFrequency (%)
0 2092
1.9%
0.01 46
 
< 0.1%
0.02 28
 
< 0.1%
0.03 39
 
< 0.1%
0.04 23
 
< 0.1%
0.05 21
 
< 0.1%
0.06 25
 
< 0.1%
0.07 22
 
< 0.1%
0.08 45
 
< 0.1%
0.09 14
 
< 0.1%
ValueCountFrequency (%)
80.19 1
< 0.1%
68.7 1
< 0.1%
57.66 1
< 0.1%
56.02 1
< 0.1%
49.36 1
< 0.1%
46.86 1
< 0.1%
46.02 1
< 0.1%
43.72 1
< 0.1%
43.7 1
< 0.1%
43.44 1
< 0.1%

Tax 3 Name
Text

MISSING 

Distinct644
Distinct (%)6.8%
Missing97868
Missing (%)91.2%
Memory size838.3 KiB
2024-02-02T12:38:46.232290image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length77
Median length66
Mean length27.433726
Min length6

Characters and Unicode

Total characters258508
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique234 ?
Unique (%)2.5%

Sample

1st rowWashington State Tax 6.5%
2nd rowSan Bernardino County District Tax Sp 0.5%
3rd rowIllinois State Tax 6.25%
4th rowSacramento Co Local Tax Sl 1%
5th rowSumner County Tax 1%
ValueCountFrequency (%)
tax 9112
19.4%
county 4123
 
8.8%
state 2629
 
5.6%
district 1844
 
3.9%
sp 1839
 
3.9%
city 1468
 
3.1%
0.5 1378
 
2.9%
1 1376
 
2.9%
san 1055
 
2.2%
los 954
 
2.0%
Other values (603) 21229
45.2%
2024-02-02T12:38:46.452266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37584
 
14.5%
a 22957
 
8.9%
t 18390
 
7.1%
o 13104
 
5.1%
n 12482
 
4.8%
i 11935
 
4.6%
e 9542
 
3.7%
T 9526
 
3.7%
% 9423
 
3.6%
x 9125
 
3.5%
Other values (61) 104440
40.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 144035
55.7%
Uppercase Letter 38378
 
14.8%
Space Separator 37584
 
14.5%
Decimal Number 21412
 
8.3%
Other Punctuation 16770
 
6.5%
Open Punctuation 164
 
0.1%
Close Punctuation 164
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 22957
15.9%
t 18390
12.8%
o 13104
9.1%
n 12482
8.7%
i 11935
8.3%
e 9542
 
6.6%
x 9125
 
6.3%
r 7093
 
4.9%
s 6975
 
4.8%
l 6899
 
4.8%
Other values (16) 25533
17.7%
Uppercase Letter
ValueCountFrequency (%)
T 9526
24.8%
S 7774
20.3%
C 7693
20.0%
D 2491
 
6.5%
L 2390
 
6.2%
A 1475
 
3.8%
I 899
 
2.3%
W 864
 
2.3%
R 749
 
2.0%
O 691
 
1.8%
Other values (16) 3826
10.0%
Decimal Number
ValueCountFrequency (%)
5 6219
29.0%
2 3724
17.4%
1 2822
13.2%
0 2768
12.9%
6 1381
 
6.4%
4 1340
 
6.3%
7 1222
 
5.7%
3 963
 
4.5%
8 647
 
3.0%
9 326
 
1.5%
Other Punctuation
ValueCountFrequency (%)
% 9423
56.2%
. 7334
43.7%
/ 7
 
< 0.1%
& 4
 
< 0.1%
' 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
37584
100.0%
Open Punctuation
ValueCountFrequency (%)
( 164
100.0%
Close Punctuation
ValueCountFrequency (%)
) 164
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 182413
70.6%
Common 76095
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 22957
 
12.6%
t 18390
 
10.1%
o 13104
 
7.2%
n 12482
 
6.8%
i 11935
 
6.5%
e 9542
 
5.2%
T 9526
 
5.2%
x 9125
 
5.0%
S 7774
 
4.3%
C 7693
 
4.2%
Other values (42) 59885
32.8%
Common
ValueCountFrequency (%)
37584
49.4%
% 9423
 
12.4%
. 7334
 
9.6%
5 6219
 
8.2%
2 3724
 
4.9%
1 2822
 
3.7%
0 2768
 
3.6%
6 1381
 
1.8%
4 1340
 
1.8%
7 1222
 
1.6%
Other values (9) 2278
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 258508
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37584
 
14.5%
a 22957
 
8.9%
t 18390
 
7.1%
o 13104
 
5.1%
n 12482
 
4.8%
i 11935
 
4.6%
e 9542
 
3.7%
T 9526
 
3.7%
% 9423
 
3.6%
x 9125
 
3.5%
Other values (61) 104440
40.4%

Tax 3 Value
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1413
Distinct (%)15.0%
Missing97868
Missing (%)91.2%
Infinite0
Infinite (%)0.0%
Mean3.7769787
Minimum0
Maximum66.57
Zeros1059
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:46.532872image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.67
median1.85
Q35.23
95-th percentile12.35
Maximum66.57
Range66.57
Interquartile range (IQR)4.56

Descriptive statistics

Standard deviation5.1003929
Coefficient of variation (CV)1.3503896
Kurtosis22.177415
Mean3.7769787
Median Absolute Deviation (MAD)1.59
Skewness3.4475199
Sum35590.47
Variance26.014007
MonotonicityNot monotonic
2024-02-02T12:38:46.588849image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1059
 
1.0%
0.74 76
 
0.1%
0.9 68
 
0.1%
1.52 67
 
0.1%
0.76 62
 
0.1%
1.8 55
 
0.1%
0.78 54
 
0.1%
0.95 50
 
< 0.1%
1.48 49
 
< 0.1%
0.38 48
 
< 0.1%
Other values (1403) 7835
 
7.3%
(Missing) 97868
91.2%
ValueCountFrequency (%)
0 1059
1.0%
0.01 15
 
< 0.1%
0.02 22
 
< 0.1%
0.03 14
 
< 0.1%
0.04 20
 
< 0.1%
0.05 13
 
< 0.1%
0.06 12
 
< 0.1%
0.07 8
 
< 0.1%
0.08 21
 
< 0.1%
0.09 8
 
< 0.1%
ValueCountFrequency (%)
66.57 1
< 0.1%
65.98 1
< 0.1%
65.51 1
< 0.1%
64.61 1
< 0.1%
63.95 1
< 0.1%
62.84 1
< 0.1%
53.06 1
< 0.1%
48.04 1
< 0.1%
44.22 1
< 0.1%
43.59 1
< 0.1%

Tax 4 Name
Text

MISSING 

Distinct295
Distinct (%)6.6%
Missing102809
Missing (%)95.8%
Memory size838.3 KiB
2024-02-02T12:38:46.705329image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length70
Median length62
Mean length28.964525
Min length15

Characters and Unicode

Total characters129819
Distinct characters69
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)3.1%

Sample

1st rowSan Bernardino County Tax 0.25%
2nd rowRegional Transport. Authority (Rta) 0.75%
3rd rowSacramento County District Tax Sp 0.5%
4th rowGeorgia State Tax 4%
5th rowUtah State Tax 4.85%
ValueCountFrequency (%)
tax 3719
16.7%
county 2888
 
13.0%
0.25 1991
 
8.9%
san 792
 
3.6%
district 747
 
3.4%
sp 746
 
3.3%
los 714
 
3.2%
angeles 714
 
3.2%
1 613
 
2.8%
state 506
 
2.3%
Other values (335) 8860
39.7%
2024-02-02T12:38:46.912391image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17808
 
13.7%
a 10339
 
8.0%
t 9178
 
7.1%
n 7530
 
5.8%
o 7019
 
5.4%
e 5475
 
4.2%
r 4955
 
3.8%
i 4764
 
3.7%
% 4482
 
3.5%
T 4246
 
3.3%
Other values (59) 54023
41.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 73579
56.7%
Uppercase Letter 18223
 
14.0%
Space Separator 17808
 
13.7%
Decimal Number 10872
 
8.4%
Other Punctuation 8370
 
6.4%
Open Punctuation 483
 
0.4%
Close Punctuation 483
 
0.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 10339
14.1%
t 9178
12.5%
n 7530
10.2%
o 7019
9.5%
e 5475
7.4%
r 4955
 
6.7%
i 4764
 
6.5%
x 3724
 
5.1%
y 3672
 
5.0%
u 3663
 
5.0%
Other values (15) 13260
18.0%
Uppercase Letter
ValueCountFrequency (%)
T 4246
23.3%
C 3913
21.5%
S 2738
15.0%
R 1360
 
7.5%
D 1328
 
7.3%
A 1262
 
6.9%
L 941
 
5.2%
O 501
 
2.7%
G 329
 
1.8%
F 230
 
1.3%
Other values (15) 1375
 
7.5%
Decimal Number
ValueCountFrequency (%)
5 3211
29.5%
0 2744
25.2%
2 2582
23.7%
1 1039
 
9.6%
4 329
 
3.0%
7 307
 
2.8%
8 307
 
2.8%
6 220
 
2.0%
3 92
 
0.8%
9 41
 
0.4%
Other Punctuation
ValueCountFrequency (%)
% 4482
53.5%
. 3840
45.9%
& 28
 
0.3%
/ 14
 
0.2%
' 6
 
0.1%
Space Separator
ValueCountFrequency (%)
17808
100.0%
Open Punctuation
ValueCountFrequency (%)
( 483
100.0%
Close Punctuation
ValueCountFrequency (%)
) 483
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 91802
70.7%
Common 38017
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 10339
 
11.3%
t 9178
 
10.0%
n 7530
 
8.2%
o 7019
 
7.6%
e 5475
 
6.0%
r 4955
 
5.4%
i 4764
 
5.2%
T 4246
 
4.6%
C 3913
 
4.3%
x 3724
 
4.1%
Other values (40) 30659
33.4%
Common
ValueCountFrequency (%)
17808
46.8%
% 4482
 
11.8%
. 3840
 
10.1%
5 3211
 
8.4%
0 2744
 
7.2%
2 2582
 
6.8%
1 1039
 
2.7%
( 483
 
1.3%
) 483
 
1.3%
4 329
 
0.9%
Other values (9) 1016
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 129819
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17808
 
13.7%
a 10339
 
8.0%
t 9178
 
7.1%
n 7530
 
5.8%
o 7019
 
5.4%
e 5475
 
4.2%
r 4955
 
3.8%
i 4764
 
3.7%
% 4482
 
3.5%
T 4246
 
3.3%
Other values (59) 54023
41.6%

Tax 4 Value
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct750
Distinct (%)16.7%
Missing102809
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean1.8481838
Minimum0
Maximum86.88
Zeros598
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:46.995475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.25
median0.5
Q31.85
95-th percentile8.797
Maximum86.88
Range86.88
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation3.5785939
Coefficient of variation (CV)1.9362759
Kurtosis89.145861
Mean1.8481838
Median Absolute Deviation (MAD)0.48
Skewness6.2879647
Sum8283.56
Variance12.806334
MonotonicityNot monotonic
2024-02-02T12:38:47.054300image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 598
 
0.6%
0.37 104
 
0.1%
0.38 103
 
0.1%
0.25 81
 
0.1%
0.24 72
 
0.1%
0.46 63
 
0.1%
0.39 62
 
0.1%
0.45 62
 
0.1%
0.19 59
 
0.1%
0.48 52
 
< 0.1%
Other values (740) 3226
 
3.0%
(Missing) 102809
95.8%
ValueCountFrequency (%)
0 598
0.6%
0.01 6
 
< 0.1%
0.02 9
 
< 0.1%
0.03 17
 
< 0.1%
0.04 14
 
< 0.1%
0.05 9
 
< 0.1%
0.06 14
 
< 0.1%
0.07 8
 
< 0.1%
0.08 21
 
< 0.1%
0.09 11
 
< 0.1%
ValueCountFrequency (%)
86.88 1
< 0.1%
42.76 1
< 0.1%
40.32 1
< 0.1%
33.19 1
< 0.1%
31.92 1
< 0.1%
30 1
< 0.1%
29.14 1
< 0.1%
28.5 1
< 0.1%
28.38 1
< 0.1%
27.06 1
< 0.1%

Tax 5 Name
Text

MISSING 

Distinct161
Distinct (%)10.8%
Missing105804
Missing (%)98.6%
Memory size838.3 KiB
2024-02-02T12:38:47.165740image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length73
Median length62
Mean length27.439139
Min length17

Characters and Unicode

Total characters40802
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)4.1%

Sample

1st rowSacramento County Tax 0.25%
2nd rowTorrance City Tax 0.5%
3rd rowLos Angeles County Tax 0.25%
4th rowScientific & Cultural Fac.(Cd) 0.1%
5th rowSan Mateo County Tax 0.25%
ValueCountFrequency (%)
tax 1230
17.5%
county 761
 
10.8%
0.25 722
 
10.3%
city 373
 
5.3%
229
 
3.3%
scientific 229
 
3.3%
0.1 229
 
3.3%
fac.(cd 229
 
3.3%
cultural 229
 
3.3%
santa 211
 
3.0%
Other values (214) 2591
36.8%
2024-02-02T12:38:47.357102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5546
 
13.6%
a 3694
 
9.1%
t 2337
 
5.7%
n 2102
 
5.2%
C 1836
 
4.5%
i 1651
 
4.0%
o 1606
 
3.9%
. 1521
 
3.7%
% 1487
 
3.6%
e 1472
 
3.6%
Other values (58) 17550
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21848
53.5%
Uppercase Letter 6004
 
14.7%
Space Separator 5546
 
13.6%
Decimal Number 3661
 
9.0%
Other Punctuation 3249
 
8.0%
Open Punctuation 247
 
0.6%
Close Punctuation 247
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3694
16.9%
t 2337
10.7%
n 2102
9.6%
i 1651
 
7.6%
o 1606
 
7.4%
e 1472
 
6.7%
u 1300
 
6.0%
x 1226
 
5.6%
y 1178
 
5.4%
l 1064
 
4.9%
Other values (16) 4218
19.3%
Uppercase Letter
ValueCountFrequency (%)
C 1836
30.6%
T 1351
22.5%
S 943
15.7%
A 272
 
4.5%
F 272
 
4.5%
L 222
 
3.7%
R 183
 
3.0%
M 148
 
2.5%
P 138
 
2.3%
O 85
 
1.4%
Other values (14) 554
 
9.2%
Decimal Number
ValueCountFrequency (%)
0 1189
32.5%
5 1048
28.6%
2 764
20.9%
1 437
 
11.9%
7 96
 
2.6%
6 37
 
1.0%
8 36
 
1.0%
4 31
 
0.8%
3 22
 
0.6%
9 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 1521
46.8%
% 1487
45.8%
& 229
 
7.0%
/ 8
 
0.2%
' 4
 
0.1%
Space Separator
ValueCountFrequency (%)
5546
100.0%
Open Punctuation
ValueCountFrequency (%)
( 247
100.0%
Close Punctuation
ValueCountFrequency (%)
) 247
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 27852
68.3%
Common 12950
31.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3694
 
13.3%
t 2337
 
8.4%
n 2102
 
7.5%
C 1836
 
6.6%
i 1651
 
5.9%
o 1606
 
5.8%
e 1472
 
5.3%
T 1351
 
4.9%
u 1300
 
4.7%
x 1226
 
4.4%
Other values (40) 9277
33.3%
Common
ValueCountFrequency (%)
5546
42.8%
. 1521
 
11.7%
% 1487
 
11.5%
0 1189
 
9.2%
5 1048
 
8.1%
2 764
 
5.9%
1 437
 
3.4%
( 247
 
1.9%
) 247
 
1.9%
& 229
 
1.8%
Other values (8) 235
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40802
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5546
 
13.6%
a 3694
 
9.1%
t 2337
 
5.7%
n 2102
 
5.2%
C 1836
 
4.5%
i 1651
 
4.0%
o 1606
 
3.9%
. 1521
 
3.7%
% 1487
 
3.6%
e 1472
 
3.6%
Other values (58) 17550
43.0%

Tax 5 Value
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct305
Distinct (%)20.5%
Missing105804
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean1.0393679
Minimum0
Maximum23.4
Zeros143
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:47.432731image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.18
median0.38
Q30.92
95-th percentile4.514
Maximum23.4
Range23.4
Interquartile range (IQR)0.74

Descriptive statistics

Standard deviation2.202723
Coefficient of variation (CV)2.119291
Kurtosis30.093215
Mean1.0393679
Median Absolute Deviation (MAD)0.26
Skewness4.8835389
Sum1545.54
Variance4.8519886
MonotonicityNot monotonic
2024-02-02T12:38:47.489323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 143
 
0.1%
0.19 48
 
< 0.1%
0.38 46
 
< 0.1%
0.39 29
 
< 0.1%
0.21 25
 
< 0.1%
0.45 25
 
< 0.1%
0.1 25
 
< 0.1%
0.25 25
 
< 0.1%
0.18 22
 
< 0.1%
0.2 22
 
< 0.1%
Other values (295) 1077
 
1.0%
(Missing) 105804
98.6%
ValueCountFrequency (%)
0 143
0.1%
0.01 2
 
< 0.1%
0.02 2
 
< 0.1%
0.03 7
 
< 0.1%
0.04 14
 
< 0.1%
0.05 10
 
< 0.1%
0.06 8
 
< 0.1%
0.07 8
 
< 0.1%
0.08 19
 
< 0.1%
0.09 15
 
< 0.1%
ValueCountFrequency (%)
23.4 1
< 0.1%
22.92 1
< 0.1%
19.02 1
< 0.1%
17.5 1
< 0.1%
16.5 1
< 0.1%
15.3 1
< 0.1%
15.2 1
< 0.1%
15.07 1
< 0.1%
14.58 1
< 0.1%
13.8 1
< 0.1%

Phone
Real number (ℝ)

MISSING 

Distinct1875
Distinct (%)32.1%
Missing101454
Missing (%)94.6%
Infinite0
Infinite (%)0.0%
Mean7.9971749 × 1010
Minimum3.5482032 × 109
Maximum8.6135434 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:47.546850image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum3.5482032 × 109
5-th percentile1.2095057 × 1010
Q11.4045503 × 1010
median1.6149351 × 1010
Q31.8135001 × 1010
95-th percentile1.973935 × 1010
Maximum8.6135434 × 1012
Range8.6099952 × 1012
Interquartile range (IQR)4.0894979 × 109

Descriptive statistics

Standard deviation6.3960231 × 1011
Coefficient of variation (CV)7.9978533
Kurtosis156.79261
Mean7.9971749 × 1010
Median Absolute Deviation (MAD)2.0657975 × 109
Skewness12.369605
Sum4.667951 × 1014
Variance4.0909112 × 1023
MonotonicityNot monotonic
2024-02-02T12:38:47.603049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.201724271 × 101051
 
< 0.1%
1.330224244 × 101030
 
< 0.1%
8.61354344 × 101228
 
< 0.1%
1.407484112 × 101028
 
< 0.1%
1.630768735 × 101027
 
< 0.1%
1.209770033 × 101026
 
< 0.1%
1.909561086 × 101024
 
< 0.1%
1.505688313 × 101023
 
< 0.1%
1.623210823 × 101023
 
< 0.1%
1.508245534 × 101023
 
< 0.1%
Other values (1865) 5554
 
5.2%
(Missing) 101454
94.6%
ValueCountFrequency (%)
3548203152 4
< 0.1%
3548691289 1
 
< 0.1%
4790862601 8
< 0.1%
6421681712 3
 
< 0.1%
6590198183 2
 
< 0.1%
6590998650 4
< 0.1%
6591292962 5
< 0.1%
6591528617 5
< 0.1%
6598637795 1
 
< 0.1%
6598769130 5
< 0.1%
ValueCountFrequency (%)
8.61354344 × 101228
< 0.1%
6.281229791 × 10121
 
< 0.1%
5.521987491 × 10121
 
< 0.1%
4.915730885 × 10128
 
< 0.1%
4.36991812 × 10122
 
< 0.1%
9.725445576 × 10115
 
< 0.1%
9.725334104 × 10115
 
< 0.1%
9.66506252 × 10114
 
< 0.1%
9.193135534 × 10116
 
< 0.1%
9.184470359 × 10112
 
< 0.1%

Receipt Number
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing107291
Missing (%)100.0%
Memory size838.3 KiB

Duties
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct163
Distinct (%)63.7%
Missing107035
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean21.249258
Minimum0
Maximum80.96
Zeros72
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size838.3 KiB
2024-02-02T12:38:47.662900image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median24.2
Q332.95
95-th percentile48.8575
Maximum80.96
Range80.96
Interquartile range (IQR)32.95

Descriptive statistics

Standard deviation16.896702
Coefficient of variation (CV)0.7951667
Kurtosis-0.1139497
Mean21.249258
Median Absolute Deviation (MAD)11.48
Skewness0.35896872
Sum5439.81
Variance285.49855
MonotonicityNot monotonic
2024-02-02T12:38:47.726205image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 72
 
0.1%
26.64 4
 
< 0.1%
27.06 4
 
< 0.1%
27.79 2
 
< 0.1%
33.3 2
 
< 0.1%
27.36 2
 
< 0.1%
35.69 2
 
< 0.1%
12.56 2
 
< 0.1%
34.2 2
 
< 0.1%
29.29 2
 
< 0.1%
Other values (153) 162
 
0.2%
(Missing) 107035
99.8%
ValueCountFrequency (%)
0 72
0.1%
1.28 1
 
< 0.1%
2.08 1
 
< 0.1%
10.04 1
 
< 0.1%
10.05 1
 
< 0.1%
10.5 1
 
< 0.1%
11 1
 
< 0.1%
11.25 1
 
< 0.1%
11.56 1
 
< 0.1%
12.18 1
 
< 0.1%
ValueCountFrequency (%)
80.96 1
< 0.1%
69.78 1
< 0.1%
66.6 1
< 0.1%
63.08 1
< 0.1%
61.36 1
< 0.1%
60.64 1
< 0.1%
58.2 1
< 0.1%
57.02 1
< 0.1%
56.04 1
< 0.1%
54.98 1
< 0.1%

Billing Province Name
Text

MISSING 

Distinct206
Distinct (%)0.5%
Missing61597
Missing (%)57.4%
Memory size838.3 KiB
2024-02-02T12:38:47.819898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length28
Median length24
Mean length8.6376986
Min length4

Characters and Unicode

Total characters394691
Distinct characters62
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)0.2%

Sample

1st rowWashington
2nd rowTexas
3rd rowNew Jersey
4th rowWisconsin
5th rowNew York
ValueCountFrequency (%)
california 7463
 
13.6%
new 5786
 
10.6%
york 3433
 
6.3%
texas 3353
 
6.1%
florida 3125
 
5.7%
jersey 1697
 
3.1%
illinois 1694
 
3.1%
pennsylvania 1681
 
3.1%
washington 1513
 
2.8%
carolina 1482
 
2.7%
Other values (230) 23467
42.9%
2024-02-02T12:38:48.096598image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 51021
12.9%
i 43612
 
11.0%
n 32857
 
8.3%
o 32832
 
8.3%
r 27253
 
6.9%
e 24004
 
6.1%
s 22610
 
5.7%
l 21559
 
5.5%
C 11041
 
2.8%
t 10710
 
2.7%
Other values (52) 117192
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 330738
83.8%
Uppercase Letter 54946
 
13.9%
Space Separator 9000
 
2.3%
Final Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 51021
15.4%
i 43612
13.2%
n 32857
9.9%
o 32832
9.9%
r 27253
8.2%
e 24004
7.3%
s 22610
6.8%
l 21559
 
6.5%
t 10710
 
3.2%
h 8431
 
2.5%
Other values (22) 55849
16.9%
Uppercase Letter
ValueCountFrequency (%)
C 11041
20.1%
N 7552
13.7%
M 4844
8.8%
T 3948
 
7.2%
Y 3434
 
6.2%
F 3194
 
5.8%
I 2904
 
5.3%
W 2536
 
4.6%
O 2425
 
4.4%
A 1928
 
3.5%
Other values (14) 11140
20.3%
Space Separator
ValueCountFrequency (%)
9000
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 385684
97.7%
Common 9007
 
2.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 51021
13.2%
i 43612
11.3%
n 32857
 
8.5%
o 32832
 
8.5%
r 27253
 
7.1%
e 24004
 
6.2%
s 22610
 
5.9%
l 21559
 
5.6%
C 11041
 
2.9%
t 10710
 
2.8%
Other values (46) 108185
28.1%
Common
ValueCountFrequency (%)
9000
99.9%
2
 
< 0.1%
. 2
 
< 0.1%
( 1
 
< 0.1%
) 1
 
< 0.1%
- 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 394670
> 99.9%
None 19
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 51021
12.9%
i 43612
 
11.1%
n 32857
 
8.3%
o 32832
 
8.3%
r 27253
 
6.9%
e 24004
 
6.1%
s 22610
 
5.7%
l 21559
 
5.5%
C 11041
 
2.8%
t 10710
 
2.7%
Other values (44) 117171
29.7%
None
ValueCountFrequency (%)
ã 7
36.8%
é 4
21.1%
ó 3
15.8%
á 2
 
10.5%
í 1
 
5.3%
ú 1
 
5.3%
ū 1
 
5.3%
Punctuation
ValueCountFrequency (%)
2
100.0%
Distinct186
Distinct (%)0.4%
Missing61866
Missing (%)57.7%
Memory size838.3 KiB
2024-02-02T12:38:48.225815image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length28
Median length24
Mean length8.6521079
Min length4

Characters and Unicode

Total characters393022
Distinct characters62
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)0.1%

Sample

1st rowWashington
2nd rowTexas
3rd rowNew Jersey
4th rowWisconsin
5th rowNew York
ValueCountFrequency (%)
california 7371
 
13.5%
new 5814
 
10.7%
york 3491
 
6.4%
texas 3296
 
6.1%
florida 3153
 
5.8%
illinois 1699
 
3.1%
pennsylvania 1679
 
3.1%
jersey 1670
 
3.1%
washington 1567
 
2.9%
carolina 1491
 
2.7%
Other values (208) 23231
42.7%
2024-02-02T12:38:48.410644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 50654
12.9%
i 43325
 
11.0%
o 32848
 
8.4%
n 32645
 
8.3%
r 27201
 
6.9%
e 23942
 
6.1%
s 22715
 
5.8%
l 21367
 
5.4%
C 10943
 
2.8%
t 10535
 
2.7%
Other values (52) 116847
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 329226
83.8%
Uppercase Letter 54746
 
13.9%
Space Separator 9037
 
2.3%
Other Punctuation 8
 
< 0.1%
Final Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 50654
15.4%
i 43325
13.2%
o 32848
10.0%
n 32645
9.9%
r 27201
8.3%
e 23942
7.3%
s 22715
6.9%
l 21367
 
6.5%
t 10535
 
3.2%
h 8374
 
2.5%
Other values (22) 55620
16.9%
Uppercase Letter
ValueCountFrequency (%)
C 10943
20.0%
N 7601
13.9%
M 4866
8.9%
T 3882
 
7.1%
Y 3492
 
6.4%
F 3248
 
5.9%
I 2896
 
5.3%
W 2567
 
4.7%
O 2375
 
4.3%
A 1945
 
3.6%
Other values (14) 10931
20.0%
Space Separator
ValueCountFrequency (%)
9037
100.0%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 383972
97.7%
Common 9050
 
2.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 50654
13.2%
i 43325
11.3%
o 32848
 
8.6%
n 32645
 
8.5%
r 27201
 
7.1%
e 23942
 
6.2%
s 22715
 
5.9%
l 21367
 
5.6%
C 10943
 
2.8%
t 10535
 
2.7%
Other values (46) 107797
28.1%
Common
ValueCountFrequency (%)
9037
99.9%
. 8
 
0.1%
2
 
< 0.1%
( 1
 
< 0.1%
) 1
 
< 0.1%
- 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 393009
> 99.9%
None 11
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 50654
12.9%
i 43325
 
11.0%
o 32848
 
8.4%
n 32645
 
8.3%
r 27201
 
6.9%
e 23942
 
6.1%
s 22715
 
5.8%
l 21367
 
5.4%
C 10943
 
2.8%
t 10535
 
2.7%
Other values (44) 116834
29.7%
None
ValueCountFrequency (%)
ã 3
27.3%
é 2
18.2%
á 2
18.2%
í 1
 
9.1%
ú 1
 
9.1%
ū 1
 
9.1%
ó 1
 
9.1%
Punctuation
ValueCountFrequency (%)
2
100.0%

Payment ID
Text

MISSING 

Distinct40677
Distinct (%)100.0%
Missing66614
Missing (%)62.1%
Memory size838.3 KiB
2024-02-02T12:38:48.519977image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length139
Median length17
Mean length19.870738
Min length8

Characters and Unicode

Total characters808282
Distinct characters69
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40677 ?
Unique (%)100.0%

Sample

1st rowc31677849043142.1
2nd rowrzA7Hrw6aJUPNcsNNmdJNkGRN
3rd rowrV4XQTBerpOSVWdVUkgHXeM9g
4th rowc31733037334726.1
5th rowrtzg5Jpm1kTawKFEgBdDqhcQ9
ValueCountFrequency (%)
1311
 
3.0%
c27162747666630.1 1
 
< 0.1%
roaezmpibjcmlfbtzyb4ss865 1
 
< 0.1%
c31625567830214.1 1
 
< 0.1%
rtyfuigad1hxysfomibxciocq 1
 
< 0.1%
r3czddw9maabjd8bt3inrl3xz 1
 
< 0.1%
rik0yhkfwoafwaybk41oulhin 1
 
< 0.1%
p1453044957382.1 1
 
< 0.1%
rgsagrimlm4rweprzxa7meaqk 1
 
< 0.1%
c31672717443270.1 1
 
< 0.1%
Other values (41979) 41979
97.0%
2024-02-02T12:38:48.688400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 72935
 
9.0%
2 68921
 
8.5%
8 48466
 
6.0%
6 48019
 
5.9%
4 45988
 
5.7%
0 45628
 
5.6%
3 44836
 
5.5%
5 43104
 
5.3%
9 42963
 
5.3%
7 41934
 
5.2%
Other values (59) 305488
37.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 502794
62.2%
Lowercase Letter 156351
 
19.3%
Uppercase Letter 114114
 
14.1%
Other Punctuation 30497
 
3.8%
Space Separator 2622
 
0.3%
Math Symbol 1311
 
0.2%
Dash Punctuation 306
 
< 0.1%
Connector Punctuation 287
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 33188
21.2%
r 13127
 
8.4%
p 6515
 
4.2%
n 6092
 
3.9%
f 4862
 
3.1%
a 4817
 
3.1%
b 4772
 
3.1%
d 4691
 
3.0%
e 4643
 
3.0%
l 4439
 
2.8%
Other values (16) 69205
44.3%
Uppercase Letter
ValueCountFrequency (%)
G 4543
 
4.0%
V 4530
 
4.0%
H 4480
 
3.9%
W 4478
 
3.9%
L 4459
 
3.9%
U 4452
 
3.9%
K 4448
 
3.9%
F 4441
 
3.9%
D 4415
 
3.9%
N 4410
 
3.9%
Other values (16) 69458
60.9%
Decimal Number
ValueCountFrequency (%)
1 72935
14.5%
2 68921
13.7%
8 48466
9.6%
6 48019
9.6%
4 45988
9.1%
0 45628
9.1%
3 44836
8.9%
5 43104
8.6%
9 42963
8.5%
7 41934
8.3%
Other Punctuation
ValueCountFrequency (%)
. 30486
> 99.9%
' 10
 
< 0.1%
# 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2622
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1311
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 306
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 287
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 537817
66.5%
Latin 270465
33.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 33188
 
12.3%
r 13127
 
4.9%
p 6515
 
2.4%
n 6092
 
2.3%
f 4862
 
1.8%
a 4817
 
1.8%
b 4772
 
1.8%
d 4691
 
1.7%
e 4643
 
1.7%
G 4543
 
1.7%
Other values (42) 183215
67.7%
Common
ValueCountFrequency (%)
1 72935
13.6%
2 68921
12.8%
8 48466
9.0%
6 48019
8.9%
4 45988
8.6%
0 45628
8.5%
3 44836
8.3%
5 43104
8.0%
9 42963
8.0%
7 41934
7.8%
Other values (7) 35023
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 808282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 72935
 
9.0%
2 68921
 
8.5%
8 48466
 
6.0%
6 48019
 
5.9%
4 45988
 
5.7%
0 45628
 
5.6%
3 44836
 
5.5%
5 43104
 
5.3%
9 42963
 
5.3%
7 41934
 
5.2%
Other values (59) 305488
37.8%

Payment Terms Name
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing107291
Missing (%)100.0%
Memory size838.3 KiB

Next Payment Due At
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing107291
Missing (%)100.0%
Memory size838.3 KiB

Payment References
Text

MISSING 

Distinct40677
Distinct (%)100.0%
Missing66614
Missing (%)62.1%
Memory size838.3 KiB
2024-02-02T12:38:48.792924image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length585
Median length17
Mean length25.574452
Min length16

Characters and Unicode

Total characters1040292
Distinct characters69
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40677 ?
Unique (%)100.0%

Sample

1st rowc31677849043142.1
2nd rowrzA7Hrw6aJUPNcsNNmdJNkGRN + c31733872132294.1 + c31733872132294.2
3rd rowrV4XQTBerpOSVWdVUkgHXeM9g + c31647884017862.1
4th rowc31733037334726.1
5th rowrtzg5Jpm1kTawKFEgBdDqhcQ9 + c31732944765126.1
ValueCountFrequency (%)
12688
 
19.2%
c23662927151302.1 2
 
< 0.1%
c28399543779526.1 2
 
< 0.1%
c24302451884230.2 2
 
< 0.1%
c25662785913030.1 2
 
< 0.1%
c25332226490566.9 2
 
< 0.1%
c24879384494278.1 2
 
< 0.1%
c25332226490566.7 2
 
< 0.1%
c25332226490566.5 2
 
< 0.1%
c24964979196102.1 2
 
< 0.1%
Other values (53331) 53347
80.8%
2024-02-02T12:38:48.966511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 93445
 
9.0%
1 93308
 
9.0%
8 63318
 
6.1%
6 62753
 
6.0%
3 62422
 
6.0%
0 61011
 
5.9%
4 60232
 
5.8%
9 56647
 
5.4%
5 56228
 
5.4%
7 54615
 
5.2%
Other values (59) 376313
36.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 663979
63.8%
Lowercase Letter 174691
 
16.8%
Uppercase Letter 121475
 
11.7%
Other Punctuation 41239
 
4.0%
Space Separator 25376
 
2.4%
Math Symbol 12688
 
1.2%
Dash Punctuation 429
 
< 0.1%
Connector Punctuation 415
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 43864
25.1%
r 13791
 
7.9%
p 6985
 
4.0%
n 6386
 
3.7%
f 5171
 
3.0%
a 5117
 
2.9%
b 5067
 
2.9%
d 4956
 
2.8%
e 4933
 
2.8%
l 4721
 
2.7%
Other values (16) 73700
42.2%
Uppercase Letter
ValueCountFrequency (%)
V 4822
 
4.0%
G 4821
 
4.0%
W 4759
 
3.9%
L 4752
 
3.9%
H 4750
 
3.9%
D 4711
 
3.9%
F 4709
 
3.9%
K 4705
 
3.9%
J 4699
 
3.9%
U 4698
 
3.9%
Other values (16) 74049
61.0%
Decimal Number
ValueCountFrequency (%)
2 93445
14.1%
1 93308
14.1%
8 63318
9.5%
6 62753
9.5%
3 62422
9.4%
0 61011
9.2%
4 60232
9.1%
9 56647
8.5%
5 56228
8.5%
7 54615
8.2%
Other Punctuation
ValueCountFrequency (%)
. 41122
99.7%
# 107
 
0.3%
' 10
 
< 0.1%
Space Separator
ValueCountFrequency (%)
25376
100.0%
Math Symbol
ValueCountFrequency (%)
+ 12688
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 429
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 415
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 744126
71.5%
Latin 296166
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 43864
 
14.8%
r 13791
 
4.7%
p 6985
 
2.4%
n 6386
 
2.2%
f 5171
 
1.7%
a 5117
 
1.7%
b 5067
 
1.7%
d 4956
 
1.7%
e 4933
 
1.7%
V 4822
 
1.6%
Other values (42) 195074
65.9%
Common
ValueCountFrequency (%)
2 93445
12.6%
1 93308
12.5%
8 63318
8.5%
6 62753
8.4%
3 62422
8.4%
0 61011
8.2%
4 60232
8.1%
9 56647
7.6%
5 56228
7.6%
7 54615
7.3%
Other values (7) 80147
10.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1040292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 93445
 
9.0%
1 93308
 
9.0%
8 63318
 
6.1%
6 62753
 
6.0%
3 62422
 
6.0%
0 61011
 
5.9%
4 60232
 
5.8%
9 56647
 
5.4%
5 56228
 
5.4%
7 54615
 
5.2%
Other values (59) 376313
36.2%

Interactions

2024-02-02T12:38:24.603255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:08.187582image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:09.278983image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:10.196559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:11.148318image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:12.077454image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:13.155602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:14.088824image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:15.024928image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:16.067449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:17.021293image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:17.959129image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:18.927220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:19.980685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:20.927736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:21.855597image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:22.740665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:23.730079image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:24.651670image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:08.265899image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:09.327824image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:10.248994image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:11.196878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:12.129501image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:13.204731image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:14.138960image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:15.078707image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:16.116282image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:17.073275image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:18.010677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:18.983068image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:20.036269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:20.981161image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:21.907138image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:22.792503image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:23.782033image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:24.702673image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:08.323506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:09.375815image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:10.299170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:11.245693image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:12.182334image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:13.255938image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:14.188729image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:15.131168image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:16.167935image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:17.122549image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:18.062997image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:19.031459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:20.086706image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:21.036422image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:21.959288image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:22.837592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:23.833323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:24.753302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:08.383364image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:09.430685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:10.355999image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:11.299261image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:12.239661image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:13.310311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:14.242867image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:15.182590image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:16.223308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:17.176905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:18.119132image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:19.085538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:20.141937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:21.089385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:22.008479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:22.999203image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:23.881123image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:24.802945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:08.444690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:09.478910image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:10.406155image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:11.347821image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:12.292084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:13.359081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:14.291859image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:15.234790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:16.275302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:17.227455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:18.171412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:19.140408image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:20.199659image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:21.146053image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:22.063598image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:23.047848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:23.929302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:24.851437image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:08.504087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2024-02-02T12:38:13.055178image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:13.986108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:14.926741image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:15.858392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:16.918878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:17.856402image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:18.827529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:19.881066image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:20.834860image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:21.763863image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:22.655635image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:23.642380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:24.510223image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:25.403964image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:09.223381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:10.143826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:11.094411image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:12.022497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:13.101480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:14.037151image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:14.974008image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:15.905827image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:16.967949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:17.903853image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:18.876840image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:19.929477image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:20.884730image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:21.812032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:22.700782image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:23.689630image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-02T12:38:24.556475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-02-02T12:38:49.045884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
SubtotalShippingTaxesTotalDiscount AmountLineitem quantityLineitem priceLineitem compare at priceRefunded AmountIdLineitem discountTax 1 ValueTax 2 ValueTax 3 ValueTax 4 ValueTax 5 ValuePhoneDutiesLineitem requires shippingLineitem taxable
Subtotal1.000-0.1780.2170.989-0.082-0.0020.0430.1020.2000.069-0.0080.2620.4510.4200.4340.4290.0360.8000.0380.016
Shipping-0.1781.000-0.133-0.109-0.1500.007-0.160-0.125-0.0390.0990.008-0.073-0.158-0.171-0.135-0.2650.104-0.4800.0810.026
Taxes0.217-0.1331.0000.2760.029-0.0150.0340.0580.0620.003-0.0050.8350.5840.5890.6010.647-0.0660.6450.0270.024
Total0.989-0.1090.2761.000-0.079-0.0020.0390.1050.1990.083-0.0080.3240.4750.4450.4560.4520.0570.8450.0520.024
Discount Amount-0.082-0.1500.029-0.0791.000-0.0040.277-0.0440.002-0.0030.0060.0350.0220.0350.0090.068-0.0200.2590.0540.029
Lineitem quantity-0.0020.007-0.015-0.002-0.0041.000-0.034-0.071-0.001-0.0020.001-0.013-0.023-0.021-0.036-0.035-0.005NaN0.0000.003
Lineitem price0.043-0.1600.0340.0390.277-0.0341.0000.7120.036-0.1430.0150.1380.0940.0830.0830.1430.0260.1560.4110.267
Lineitem compare at price0.102-0.1250.0580.105-0.044-0.0710.7121.0000.0020.265-0.3290.0130.0740.031-0.0090.0030.026-0.3880.0260.019
Refunded Amount0.200-0.0390.0620.1990.002-0.0010.0360.0021.000-0.0120.0010.0730.1110.1010.1070.127-0.0010.1210.0200.007
Id0.0690.0990.0030.083-0.003-0.002-0.1430.265-0.0121.000-0.014-0.279-0.028-0.0100.0310.011-0.0440.0700.2550.413
Lineitem discount-0.0080.008-0.005-0.0080.0060.0010.015-0.3290.001-0.0141.0000.001-0.006NaNNaNNaN-0.007NaN0.0380.025
Tax 1 Value0.262-0.0730.8350.3240.035-0.0130.1380.0130.073-0.2790.0011.0000.1080.0910.1740.503-0.0020.6640.0530.000
Tax 2 Value0.451-0.1580.5840.4750.022-0.0230.0940.0740.111-0.028-0.0060.1081.0000.3720.4410.395-0.0300.2800.0000.018
Tax 3 Value0.420-0.1710.5890.4450.035-0.0210.0830.0310.101-0.010NaN0.0910.3721.0000.3800.379-0.1870.8400.0000.000
Tax 4 Value0.434-0.1350.6010.4560.009-0.0360.083-0.0090.1070.031NaN0.1740.4410.3801.0000.119-0.083NaN0.0110.000
Tax 5 Value0.429-0.2650.6470.4520.068-0.0350.1430.0030.1270.011NaN0.5030.3950.3790.1191.0000.061NaN0.0840.035
Phone0.0360.104-0.0660.057-0.020-0.0050.0260.026-0.001-0.044-0.007-0.002-0.030-0.187-0.0830.0611.0000.4530.0150.000
Duties0.800-0.4800.6450.8450.259NaN0.156-0.3880.1210.070NaN0.6640.2800.840NaNNaN0.4531.0000.0631.000
Lineitem requires shipping0.0380.0810.0270.0520.0540.0000.4110.0260.0200.2550.0380.0530.0000.0000.0110.0840.0150.0631.0000.665
Lineitem taxable0.0160.0260.0240.0240.0290.0030.2670.0190.0070.4130.0250.0000.0180.0000.0000.0350.0001.0000.6651.000

Missing values

2024-02-02T12:38:25.956738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-02T12:38:26.962851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-02-02T12:38:29.770216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

NameEmailFinancial StatusPaid atFulfillment StatusFulfilled atAccepts MarketingCurrencySubtotalShippingTaxesTotalDiscount CodeDiscount AmountShipping MethodCreated atLineitem quantityLineitem nameLineitem priceLineitem compare at priceLineitem skuLineitem requires shippingLineitem taxableLineitem fulfillment statusBilling NameBilling StreetBilling Address1Billing Address2Billing CompanyBilling CityBilling ZipBilling ProvinceBilling CountryBilling PhoneShipping NameShipping StreetShipping Address1Shipping Address2Shipping CompanyShipping CityShipping ZipShipping ProvinceShipping CountryShipping PhoneNotesNote AttributesCancelled atPayment MethodPayment ReferenceRefunded AmountVendorIdTagsRisk LevelSourceLineitem discountTax 1 NameTax 1 ValueTax 2 NameTax 2 ValueTax 3 NameTax 3 ValueTax 4 NameTax 4 ValueTax 5 NameTax 5 ValuePhoneReceipt NumberDutiesBilling Province NameShipping Province NamePayment IDPayment Terms NameNext Payment Due AtPayment References
0#75662amomda16@gmail.compaid2023-12-31 20:45:05 -0800fulfilled2024-01-03 10:20:02 -0800noUSD208.750.021.2229.95RWRD1UMFXV92IH15.0Standard Shipping (5-10 business days)2023-12-31 20:45:04 -08001Onward VIP Protection+ - $8.758.75NaNONWARDINS40FalseFalsefulfilledAmanda Dorgan4529 185th Pl SW4529 185th Pl SWNaNNaNLynnwood'98037WAUS(425) 239-3205Amanda Dorgan4529 185th Pl SW4529 185th Pl SWNaNNaNLynnwood'98037WAUS(425) 239-3205NaNlc_anon_id: 83a291af-ba4f-4cd6-fec2-2b14713ebb8d\nexported: fulfilled_by_verteNaNShopify Paymentsc31677849043142.10.0Onward5.454060e+12OnwardLowweb0.0Lynnwood City Tax 4.1%8.2Snohomish County Tax 0%0.0Washington State Tax 6.5%13.0NaNNaNNaNNaNNaNNaNNaNWashingtonWashingtonc31677849043142.1NaNNaNc31677849043142.1
1#75662amomda16@gmail.comNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2023-12-31 20:45:04 -08001Stelo Chrome Gold - 6-6.525.00NaN665HO21STCHGTrueTruefulfilledNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2#75662amomda16@gmail.comNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2023-12-31 20:45:04 -08001The D'Orsay - Forest Velvet + Stiletto Heel Kit 3 Forest Green - 6.5190.00190.065HO21DOFVS3FGTrueTruefulfilledNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3#75661kmgnadinger@gmail.comrefunded2023-12-31 19:17:28 -0800unfulfilledNaNyesUSD455.000.00.0455.00NaN0.0Standard Shipping (5-10 business days)2023-12-31 19:17:26 -08001Stiletto Heel Kit 4 Whiskey - 9-1135.00NaN911HO21HKS4WHTrueTruependingKatherine Gnadinger7011 Chackbay Ln7011 Chackbay LnNaNNaNDallas'75227TXUS+18176882853Andi Baritchi12481 Pleasant Hill Ln12481 Pleasant Hill LnNaNNaNFrisco'75033TXUS+18176882853NaNlc_anon_id: 5490dd6f-0b52-45a7-ea72-793a0cded0d8\nexported: exported2024-01-17 08:27:45 -0800Shopify PaymentsrzA7Hrw6aJUPNcsNNmdJNkGRN455.0Pashion Footwear5.454007e+12High refund, High Volume CustomerLowweb0.0Texas State Tax 0%0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNTexasTexasrzA7Hrw6aJUPNcsNNmdJNkGRNNaNNaNrzA7Hrw6aJUPNcsNNmdJNkGRN + c31733872132294.1 + c31733872132294.2
4#75661kmgnadinger@gmail.comNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2023-12-31 19:17:26 -08001Block Heel Kit 4 Coal - 9-1140.00NaN911HO21HKB4COTrueTruependingNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
5#75661kmgnadinger@gmail.comNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2023-12-31 19:17:26 -08001The Pashionista - Coal Leather + Stiletto Heel Kit 3 Coal - 9190.00NaN9HO21PACLS3COTrueTruependingNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
6#75661kmgnadinger@gmail.comNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2023-12-31 19:17:26 -08001The Pashionista - Whiskey Leather + Block Heel Kit 4 Whiskey - 9190.00NaN9HO21PAWHLB4WHTrueTruependingNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
7#75660jwheaton713@gmail.compaid2023-12-31 18:46:11 -0800fulfilled2024-01-03 10:20:01 -0800yesUSD180.000.00.0180.00WELCOMEBACK2045.0Standard Shipping (5-10 business days)2023-12-31 18:46:08 -08001The Bootie - Coal Knit + Block Heel Kit 4 Coal - 7.5225.00NaN75HO21TBCKB4COTrueTruefulfilledJessica Wheaton1009 11th Avenue1009 11th AvenueNaNNaNDorothy'08317NJUS+6096029822Jessica WheatonPO Box 151PO Box 151NaNNaNDorothy'08317NJUS+6096029822NaNlc_anon_id: d6b67c21-cac3-4bbb-c1bb-64b511954ba8\nexported: fulfilled_by_verteNaNShopify PaymentsrV4XQTBerpOSVWdVUkgHXeM9g0.0Pashion Footwear5.453985e+12NaNLowweb0.0New Jersey State Tax 0%0.0NaNNaNNaNNaNNaNNaNNaNNaN1.609603e+10NaNNaNNew JerseyNew JerseyrV4XQTBerpOSVWdVUkgHXeM9gNaNNaNrV4XQTBerpOSVWdVUkgHXeM9g + c31647884017862.1
8#75659slambertini107@yahoo.compaid2023-12-31 17:17:54 -0800fulfilled2024-01-03 10:20:02 -0800yesUSD93.750.00.093.75NaN0.0Standard Shipping (5-10 business days)2023-12-31 17:17:54 -08001Onward VIP Protection+ - $3.753.75NaNONWARDINS15FalseFalsefulfilledSarah Lambert924 E Juneau Avenue, Unit 502924 E Juneau AvenueUnit 502NaNMilwaukee'53202WIUS(414) 943-1231Sarah Lambert924 E Juneau Avenue, Unit 502924 E Juneau AvenueUnit 502NaNMilwaukee'53202WIUS(414) 943-1231NaNReferral: \nReferral Other: \nReferral Influencer: \nexported: fulfilled_by_verteNaNPayPal Express Checkoutc31733037334726.10.0Onward5.453915e+12OnwardLowweb0.0Wisconsin State Tax 0%0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNWisconsinWisconsinc31733037334726.1NaNNaNc31733037334726.1
9#75659slambertini107@yahoo.comNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2023-12-31 17:17:54 -08001Block Heel Kit 4 Light Wood - 9-1140.00NaN911HO21HKB4LWTrueTruefulfilledNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
NameEmailFinancial StatusPaid atFulfillment StatusFulfilled atAccepts MarketingCurrencySubtotalShippingTaxesTotalDiscount CodeDiscount AmountShipping MethodCreated atLineitem quantityLineitem nameLineitem priceLineitem compare at priceLineitem skuLineitem requires shippingLineitem taxableLineitem fulfillment statusBilling NameBilling StreetBilling Address1Billing Address2Billing CompanyBilling CityBilling ZipBilling ProvinceBilling CountryBilling PhoneShipping NameShipping StreetShipping Address1Shipping Address2Shipping CompanyShipping CityShipping ZipShipping ProvinceShipping CountryShipping PhoneNotesNote AttributesCancelled atPayment MethodPayment ReferenceRefunded AmountVendorIdTagsRisk LevelSourceLineitem discountTax 1 NameTax 1 ValueTax 2 NameTax 2 ValueTax 3 NameTax 3 ValueTax 4 NameTax 4 ValueTax 5 NameTax 5 ValuePhoneReceipt NumberDutiesBilling Province NameShipping Province NamePayment IDPayment Terms NameNext Payment Due AtPayment References
107281#29283iwilleatchu7@gmail.compaid2021-12-01 06:46:18 -0800fulfilled2021-12-11 10:04:19 -0800noUSD162.00.00.00162.00Welcome2Pashion18.0Free Standard Shipping (5-10 business days)2021-12-01 06:46:17 -080014 Inch Block Heel Kit Light Wood - 7-8.535.040.0785SU20HKLW4BTrueTruefulfilledAlana Nolte3740 Jones Ferry Lane3740 Jones Ferry LaneNaNNaNAlpharetta'30022GAUS6787909468Alana Nolte3740 Jones Ferry Lane3740 Jones Ferry LaneNaNNaNAlpharetta'30022GAUS6787909468NaNNaNNaNShopify Paymentsc23582782423238.10.0Pashion Footwear4.336973e+12NaNLowweb0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNGeorgiaGeorgiac23582782423238.1NaNNaNc23582782423238.1
107282#29283iwilleatchu7@gmail.comNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2021-12-01 06:46:17 -08001The Sandal - Coal Leather Stiletto 4 Inch - 8.5145.0185.085SP20VICOML4TrueTruefulfilledNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
107283#29282michaelkozik@live.compaid2021-12-01 06:35:51 -0800fulfilled2021-12-09 09:05:09 -0800noUSD130.50.00.00130.50Welcome2Pashion14.5Free Standard Shipping (5-10 business days)2021-12-01 06:35:50 -08001The Sandal - Latte Leather Block 3 Inch - 9.5145.0185.095SP21TSLL3BTrueTruefulfilledMichael K. Kozik4001 SANDPIPER CT N4001 SANDPIPER CT NNaNNaNVALPARAISO46385-6321INUS219-921-4826Michael K. Kozik4001 SANDPIPER CT N4001 SANDPIPER CT NNaNNaNVALPARAISO46385-6321INUS219-921-4826NaNNaNNaNAmazon Payc23582629036230.10.0Pashion Footwear4.336957e+12NaNLowweb0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNIndianaIndianac23582629036230.1NaNNaNc23582629036230.1
107284#29281apurvis@mfah.orgpaid2021-12-01 06:25:19 -0800fulfilled2021-12-08 16:22:14 -0800noUSD595.00.00.00595.00NaN0.0Free Standard Shipping (5-10 business days)2021-12-01 06:25:17 -08001The D'Orsay Latte Patent Block 4 Inch - 8140.0185.08SU21DOLT4BTrueTruefulfilledAmy Purvis3138 Newcastle Dr3138 Newcastle DrNaNNaNHouston'77027TXUS(281) 974-8450Amy Purvis3138 Newcastle Dr3138 Newcastle DrNaNNaNHouston'77027TXUS(281) 974-8450NaNReferral Other: +1 281-974-8450\nReferral Influencer: +1 281-974-8450NaNShopify Paymentsc23582558585030.10.0Pashion Footwear4.336941e+12High Volume CustomerLowweb0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNTexasTexasc23582558585030.1NaNNaNc23582558585030.1
107285#29281apurvis@mfah.orgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2021-12-01 06:25:17 -08001D'Orsay - Coal Leather Stiletto 4 Inch - 8175.0195.08HO20DOBL4STrueTruefulfilledNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
107286#29281apurvis@mfah.orgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2021-12-01 06:25:17 -08001The Sandal - Sand Patent Block 4 Inch - 8135.0175.08SU20TSSA4BTrueTruefulfilledNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
107287#29281apurvis@mfah.orgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2021-12-01 06:25:17 -08001The Sandal - Coal Leather Block 4 inch - 8145.0185.08SU21TSCL4BTrueTruefulfilledNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
107288#29280jstraveler26@hotmail.compaid2021-12-01 00:38:19 -0800fulfilled2021-12-08 16:22:09 -0800noUSD157.50.011.43168.93Welcome2Pashion17.5Free Standard Shipping (5-10 business days)2021-12-01 00:38:18 -080014 Inch Stiletto Heel Kit Coal - 7-8.520.035.0785SP19HKCO4TrueTruefulfilledJudy Susser-Travis510 Stratford Court A308510 Stratford Court A308NaNNaNDel Mar'92014CAUS+18584841982Judy Susser-Travis510 Stratford Court A308510 Stratford Court A308NaNNaNDel Mar'92014CAUS+18584841982NaNNaNNaNShopify Paymentsc23578658308294.10.0Pashion Footwear4.336528e+12NaNLowweb0.0California State Tax 7.25%11.43NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNCaliforniaCaliforniac23578658308294.1NaNNaNc23578658308294.1
107289#29280jstraveler26@hotmail.comNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2021-12-01 00:38:18 -080013 Inch Stiletto Heel Kit Coal - 7-8.520.035.0785SP19HKCO3STrueTruefulfilledNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
107290#29280jstraveler26@hotmail.comNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2021-12-01 00:38:18 -08001The Sandal - Neutral Snake 4 Inch Block - 8.5135.0175.085FA21TSNSK4BTrueTruefulfilledNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPashion FootwearNaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

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